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MODEL SCHEME OF STUDIES FOR BS (4-YEAR) IN STATISTICS

MODEL SCHEME OF STUDIES FOR BS (4-YEAR) IN STATISTICS

MODEL SCHEME OF STUDIES FOR BS (4-YEAR) IN STATISTICS


Semester   /    Name of Subject                                Credits 

  Year 

First


           Introductory Statistics                              3 

                  Pakistan Studies                                     2 

                  English-I (Functional English)                       3 

                  Calculus-I                                           3 

                  General-I                                            3 

                  General-II                                           3 

                                                                      17 

 Second


           Introduction to Probability Distributions            3 

                  Islamic Studies/Ethics                               2 

                  English-II                                           3 

                  Calculus-II                                          3 

                  General-III                                          3 

                  General-IV                                           3 

                                                                      17 

Third


             Basic Statistical Inference                          3 

                  English-III                                          3 

                  Introduction to Computer                             3 

                  General-V                                            3 

                  General-VI                                           3 

                                                                      15 

Fourth    


        Applied Statistics                                   3 

                  Introduction   to   Regression   Analysis   &        3 

                                                     Experimental Design 

                  Communication Skills                                 3 

                  Linear Algebra                                       3 

                  General-VII                                          3 

                                                                      15 

 Fifth


            Probability Distribution-1                           3 

                  Sampling Technique-I                                 4 

                  Design & Analysis of Experiment-I                    4 

                  Regression Analysis                                  4 

                  Statistical Packages                                 3 

                                                                      18 

  Sixth 


          Probability Distribution-II                          3 

                  Sampling Techniques-II                               4 

                  Design & Analysis of Experiment-II                   4 
 Econometrics                                            4 

                   Official Statistics                                      3 

                                                                           18

Seventh  


           Statistical Inference-1                                  3 

                   Applied Multivariate Analysis                            4 

                   Time Series Analysis                                     3 

                    Elective I                                              3 

                    Elective-II                                             3 

                                                                           16 

   Eight 


          Statistical Inference-II                                 3 

                    Population Studies                                      4 

                    Research Project / Internship                           3 

                    Elective-III                                            3 

                    Elective-IV                                             3 

                                                                           16 

                   Total                                                  132 


Note: 4 credit hours courses must include Lab. /Practical. 



Aims and Objectives 



The major aims and objectives of the curriculum of Statistics are to adapt 

the curriculum to meet the international standards. 



1.   To  provide  a  sound  footing  of  the  subject  matter  of  statistical  theory 

     with applications, so that the students can pursue higher degrees and 

     research in the field of statistics. 



2.   To train the students in the use of statistical software and techniques of 

     data  collection  and  analysis  so  that  they  can  compete  in  the  job 

     market. 



3.   To involve the students in research project so that they can be better 

     trained in the field of research. 



4.   To develop a solid foundation for the effective operational and strategic 

     decisions based on statistical theory and methodology in almost every 

     discipline. 
* LIST OF GENERAL COURSES FOR STATISTICS 



Seven  courses  are  to  be  selected  from  the  following  list  of  courses, 

according to available facilities and faculty of the universities. 



1.       Business Administration (Entrepreneurship) 

2.       Human Resource Management 

3.       Environmental Sciences 

4.       Principles of Management & Marketing 

5.       Basic Financial Management 

6.       History of Human Civilization 

7.       Introduction to Biology 

8.       Foreign Language other than English 

9.       Introduction to Physics 

 10.     Advanced Calculus 

 11.     Introduction to Genetics 

 12.     Introduction to Geography 



or any other subject depending upon the expertise available. 

DETAIL OF COURSES 




The proposed outlines of the BS (4-YEAR) programme in Statistics are as 

follows: 



STAT- 101:         Introductory Statistics - I 



The nature and scope of the Statistics, Variables and their types, Data and 

its sources, Scales of measurements, Tabulation and classification of data, 

Graphs  and  Charts:  Stem-and  leaf  diagram,  Box  and  Whisker  plots  and 

their interpretation.  Measures of Central Tendency, Quantiles, Meaures of 

Dispersion: Their properties, usage, limitations and comparison. Moments, 

Measures  of  Skewness  and  Kurtosis  and  Distribution  shapes.  Rates  and 

ratios, Standardized scores 



Recommended Books 



     1.  A basic course  in statistics / G.M. Clarke, D. Cooke.  Edition:  5th 

         ed. Publisher: London : John Wiley, 2004 

     2.   Chaudhry,  S.M.and  Kamal,  S.  (2008),  “Introduction  to  Statistical 

          Theory” Parts I & II, 8th  ed, Ilmi Kitab Khana, Lahore, Pakistan. 

     3.   Mann, P. S. (2010) Introductory Statistics. Wiley. 

     4.   Mclave,  J.T.,Benson,  P.G.  and  Snitch,  T.  (2005)  “Statistics  for 

         Business & Economics” 9th        ed.  Prentice Hall, New Jersey. 

     5.  Schaum's outline of theory and  problems of beginning statistics / 

          Larry J. Stephens. Edition: 2nd ed. Publisher: New York : McGraw- 

          Hill, 2006 

     6.  Spiegel,    M.R.,    Schiller,   J.L.   and    Sirinivasan,    R.L.   (2000) 

         “Probability  and  Statistics”,  2nd    ed.  Schaums  Outlines  Series. 

          McGraw Hill. NY. 

     7.  Sullivan,   M.,   Fundamentals   of   statistics,   III.   Edition:   3rd   ed. 

          Publisher: Boston: Prentice Hall, 2011. 

     8.  Walpole, R.E., Myers, R.H and Myers, S.L. (1998), “Probability and 

          Statistics for Engineers and Scientist” 6th  edition, Prentice Hall, NY. 

     9.  Weiss, N.A.(1997), “Introductory Statistics” 4th  ed. Addison-Wesley 

          Pub. Company, Inc. 

     10. 



STAT- 102:         Introduction         to    Probability        &     Probability 

                   Distributions 



Probability Concepts, Addition and Multiplication rules, bivariate frequency 

tables,   joint  and    marginal    probabilities,   Conditional    probability    and 

independence, Bayes’ rule 



Random Variables, Discrete Probability Distribution, Mean and Variance of 

a  discrete  random  variable,  Bernoulli  trials,  Properties,  applications  and 

fitting   of   Binomial,   Poisson,  Hypergeometric,   Negative   Binomial   and 

Geometric distributions 
Continuous      Random      Variable,   probability    density   function    and   its 

properties, Normal Distribution and its properties, Standard Normal Curve 



Recommended Books: 



1.   Cacoullos, T., Exercises in probability, Publisher: New York: Springer- 

     Verlag, 2009 



2.    Chaudhry,   S.M.and   Kamal,  S.  (2008),  “Introduction  to  Statistical 

     Theory” Parts I & II, 8th   ed, Ilmi Kitab Khana, Lahore, Pakistan. 



3.   Mann, P. S. (2010) Introductory Statistics. Wiley. 

4.   Clark, G.M. and Cooke, D. (1998), “A Basic Course in Statistics” 4th  ed, 

     Arnold, London. 



5.   Mclave,   J.T.,   Benson,   P.G.   and   Snitch,   T.   (2005)   “Statistics   for 

     Business & Economics” 9th       Edition.  Prentice Hall, New Jersey. 



6.    Santos.D.,  Probability:  an  introduction,  Publisher:  Sudbury,  Mass.: 

     Jones and Bartlett Publishers, c2011. 



7.    Spiegel,  M.R., Schiller, J.L. and Sirinivasan, R.L. (2000) “Probability 

     and Statistics”, 2nd  ed. Schaums Outlines Series. McGraw Hill. NY. 



8.    Walpole,  R.E.,  Myers,  R.H  and  Myers,  S.L.  (2007),  “Probability  and 

     Statistics for Engineers and Scientist” 7th  edition, Prentice Hall, NY. 



9.   Weiss,  N.A.  (1997),    “Introductory  Statistics”  4th ed.  Addison-Wesley 

     Pub. Company, Inc. 



STAT- 202:         Basic Statistical Inference 



Sampling  distribution:  concepts  and  properties,  Central  limit  theorem. 

Estimation:  Point  Estimation.  Desirable  Properties  of  a  Good  Estimator, 

Interval  Estimation,   Interval  Estimation  of  population  mean.  Large  and 

small sample confidence intervals for Population Mean 



Nature of Hypothesis Testing and Types of errors,  Hypothesis Testing for 

Population Mean and variance 



Inferences  for  Two  Population  Means,  Large-sample  inferences  for  Two 

Populations using Independent Samples,  Inferences for the Mean of Two 

Normal Populations  using  Independent  Samples (variances are assumed 

Equal/Not   Equal).  Inference  for  Two  Populations  Mean   using  Paired 

Samples 



Inferences for Population Proportions, Confidence Intervals and hypothesis 

testing   for  Population     Proportion,    Inferences     for  Two     Populations 

Proportions using Independent Samples, Estimation of sample size Pre-Requisite- STAT-102 



Recommended Books: 



1.     Chaudhry,  S.M.  and  Kamal,  S.  (2008),  “Introduction  to  Statistical 

       Theory” Part I, II, 8th  ed, Ilmi Kitab Khana, Lahore, Pakistan. 



2.     Clark, G.M. and Cooke, D. (1998), “A Basic Course in Statistics” 4th 

       ed, Arnold, London. 



3.     Mclave,  J.T.,  Benson  P.G.  and  Snitch,  T.  (2005)  “Statistics  for 

       Business & Economics” 9th  Prentice Hall New Jersey. 



4.     Spiegel, M.R., Schiller, J.L. and Sirinivasan, R.L. (2000) “Probability 

       and Statistics”, 2nd  ed. Schaums Outlines Series. McGraw-Hill. NY. 



5.     Walpole, R.E., Myers, R.H. and Myers, S.L. (2007), “Probability and 

       Statistics for Engineers and Scientist” 7th  edition, Prentice Hall, NY. 



6.     Weiss, N.A. (1997), “Introductory Statistics” 4th     ed. Addison-Wesley 

       Pub. Company, Inc. 



STAT- 203:        Introduction         to   Regression          Analysis       and 

                  Experimental Design 



Concepts   of   Regression   and   Correlation,   Simple   Linear   regression, 

multiple  linear  regression,  Inference  regarding  regression  parameters, 

linear   correlation:   simple,   partial   and   multiple   correlation, Inference 

regarding correlation coefficient, Coefficient of determination 



One-Way and Two-Way Analysis of Variance 



Design   of   Experiments,   Basic   Principles   of   Design   of   Experiments, 

Description,  Layout  and   Analysis  of  Completely   Randomized  Design, 

Randomized  Complete  Block  Design  and  Latin  Square  Design,  Multiple 

Comparisons (LSD and Duncan’s test) 



Pre-Requisite: STAT-101 



Recommended Books: 



1.     Chaudhry,  S.M.,  and  Kamal,  S.,  (2009),  “Introduction  to  Statistical 

       Theory” Part I, II, 8th  ed, Ilmi Kitab Khana, Lahore, Pakistan. 



2.     Clark, G. M. and Kempston, R. E. (1997), “Introduction to the Design 

       & Analysis of Experiment” Arnold London. 



3.     Walpole,  P.E.,  Myers  R.H.,  Myers  S.L.  (2007),  “Probability  and 

       Statistics for Engineers and Scientists”,     7th  ed. Prentice Hall. 

4.     Weiss, N.A, (1997), “Introductory Statistics” 4th     ed. Addison-Wesley 

       Pub. Company, Inc. 
STAT- 201:         Applied Statistics 



Sampling: Sample versus  population, Sampling,  advantages of sampling, 

statistic and parameter. Probability sampling techniques: Simple Random 

sampling,   Stratified   random   sampling,   Systematic   random   sampling, 

Cluster  Sampling.  Non-probability  sampling  techniques:  Quota  sampling, 

purposive  sampling,  Snowball  sampling.  Census  and  survey  problem, 

framing of questionnaire, Sampling and Non-Sampling Errors 



Index  numbers:  construction  and  uses  of  index  numbers,  un-weighted 

index numbers (simple aggregative index, average of relative  price index 

numbers), weighted index numbers (Laspayers, Paaches and Fishers ideal 

index numbers), Consumer price index (CPI) and Sensitive Price Indicators 



Time Series Analysis: Components of time series and their decomposition. 



Vital Statistics : Meaning of vital statistics, registrations of Birth and death in 

Pakistan. Uses of vital statistics, short comings of vital statistics, rates and 

ratios (Sex ratio, child women ratio, birth and death ratio, population growth 

rate, classification of natal rates, death rates or mortality rates, crude death 

rate,  specific  death  rate,  infant  mortality  rate,  case  fatality  rate,  fertility 

rates,   crude   birth   rate,   specific   birth   rate,   standardized   death   rate, 

reproduction  rates,  morbidity  or  sickness  rates,  marriage  rates,  divorce 

rates etc. general; fertility rate, total fertility rate.) 



Pre-Requisite: STAT-101 



Recommended Books: 



1.     Chaudhry,  S.M.  and  S.  Kamal,  (2009),  “Introduction  to  Statistical 

        Theory” Part I, II, 8th  Ed, IImi Kitab Khana, Lahore, Pakistan. 

2.     Clark, G.M. and Cooke, D. (1998), “A Basic Course in Statistics” 4th 

       ed, Arnold, London. 

3.     Cochran, W.G. (1977) “Sampling Techniques”.3rd  Ed. 



4.     Mclave,  J.T.  Benson,  P.G.  and  Snitch,  T.  (2005)  “Statistics  for 

       Business & Economics” 9th  Edition, Prentice Hall, New Jersey. 



5.     Pollard,  A.H.   Yousuf,  F.  and  Pollard  G.M.  (1982),  “Demographic 

        Techniques”, Pergamon Press, Sydney. 



6.     Walpole,  P.E.  Myers,  R.H.,  Myers  S.L.  (1998),  “Probability  and 

       Statistics for Engineers and Scientists”, Prentice Hall. 
STAT- 204:        Statistical Packages 



Introduction    to  Minitab,   data    manipulation    in   Minitab,   graphical 

representation  in  Minitab,  Qualitative  and  Quantitative  data  presentation 

and analyzing data in Minitab, Programming in Minitab 



Introduction  of  SPSS,  data  manipulation  in  SPSS,  simple  arithmetic  in 

SPSS,  SPSS  function  related  to  probability  distributions,  SPSS  modules, 

simple graphing in SPSS 



Analysis using SPSS syntax programming 



Note:  Use of any  other statistical  package based upon the availability of 

the Software. 



Pre-Requisite: STAT-202 



Recommended Books: 



1.     Colin  D.  Gray  and  Paul  R.  Kinnear,  IBM  SPSS  statistics  19  made 

       simple. Publisher: New York: Psychology Press, 2012. 



2.     Kerr A. W., Hall, H. K., and Kozub, S. A. (2002) Doing Statistics with 

       SPSS. Sage Publications. 



3.     SPSS (2010) SPSS Statistics 19 Core System User’s Guide. 



4.     Marques de Sá, Joaquim P.( 2003)  Applied Statistics using SPSS, 

       STATISTICA and MATLAB 



5.     Norusis, Marija (2006) SPSS 14.0 Guide to Data Analysis, Prentice 

       Hall, New Jersey. 



6.     Ryan,  Barbara  F.;  Joiner,  Brian  L.  and  Cryer,  Jonathan  D.(2005) 

       MINITAB Handbook, 5th Edition, Duxbury Press, California. 



7.     Susan  A.  Nolan  and  Thomas  E.  Heinzen.    Study  Guide  &  SPSS 

       Manual to accompany    statistics for the behavioral sciences Edition: 

       2nd ed. Publisher: New York : Worth Publishers, 2012 



STAT- 301:        Probability Distributions-I 



Distribution  function,  Probability  mass  function  and  probability  density 

function.  Joint  and  conditional  distributions  for  two  and  more  random 

variables, Marginal and conditional distributions, stochastic independence, 

Baye’s  theorem,  Mathematical  expectation  and  its  properties  Conditional 

expectation,   variance   and   moments,     Probability  generating   function, 

Moment     generating   and   characteristic   functions   and   their   properties, 

Relation  between  moments  and  cummulants,          Probability  distributions: 

Bernoulli,   Binomial,    Hypergeometric,      Poisson,    Negative    binomial, Geometric,  Multinomial  distribution.  Normal  approximation  to  binomial  & 

Poisson distribution, Normal distribution with moments and cummulants 



Pre-Requisite:             STAT-102 



Recommended Books 



1.     Fridett,  B.  &  Gray,  L.  (1997).  “A  Modern  Approach  to  Probability 

       Theory” Birkhallser, Boston. 



2.     Freund,  J.  E.  (1997).  “Mathematical  Statistics”,  Prentice  Hall,  New 

       Jersey 6th  edition. 



3.     Haq, M. (1984). Foundation of Probability and Statistics, Tahir sons, 

       Urdu Bazar, Karachi. 



4.     Hirai, A.S. (2002), “A Course in Mathematical Statistics”,  Ilmi Kutab 

       Khana, Lahore. 



5.        Hogg,  R.M.  and  Craig,  A.T.  (1995),  “Introduction  to  Mathematical 

       Statistics”. Prentice Hall, Engle wood Cliffs, New Jersey. 



6.     Khan,  M.  K.,  (1996).  “Probability  with  Applications”,  Maktiba  Ilmi, 

       Lahore. 



7.     Mood, A.M, Graybill, F.A. and Boes, D.C. (1997), “Introduction to the 

       Theory of Statistics”, McGraw Hill, New York. 



10.    Norman      L.   Johnson , Samuel       Kotz , N.    Balakrishnan (1994). 

       Continuous     Univariate   Distributions,   Vol.   1  (Wiley    Series   in 

       Probability and Statistics), Wiley-Interscience: New York. 



11.    Samuel     Kotz , N.    Balakrishnan, Norman       L.   Johnson     (2000). 

       Continuous     Multivariate   Distributions,  Volume     1,  Models     and 

       Applications, 2nd Edition, Wiley-Interscience: New York. 



12.    Sheldon  Ross (2009).  First  Course  in   Probability,  (8th   Edition), 

       Pearson 

      Stirzaker, D. (1999). “Probability and Random Variables”. Cambridge 

       University Press, Cambridge. 



13.    Stuart,  A.  and  Ord,  J  .K.  Kendall’s’  (1998),  “Advanced  Theory  of 

       Statistics”, Vol. I, Charles Griffin, London. 



STAT- 303:        Sampling Techniques-I 



Advantages  of  sampling,  requirements  of  a  good  sample,  bias,  sampling 

and  non-sampling  errors,  Steps  and  problems  involved  in  planning  and 

conduct  of  census  and  their  sources,  sample  surveys,        Selection  and 

estimation   procedures.   Description   and   properties    of   simple   random 

sampling,    Sampling   for   proportions   and   percentages,     Estimation   of variances,    standard    errors   and    confidence    limits,  Sample     size 

determination  under    different  conditions, Description  and  properties  of 

stratified  random  sampling,   Formation  of  strata,  Different  methods  of 

allocation  of  sample  size,  Systematic  sampling,    Ratio  and  regression 

estimates in simple and stratified random sampling 



Pre-Requisite:            STAT-201 



Recommended Books: 



1.   Brewer, K. R. & Hanif, M. (1983). Sampling with Unequal Probabilities, 

       Lecture Notes in Statistics Series, No. 15, Springer Verlag. 



2.     Bethelem,    J.  (2009)   Applied    Survey   Methods:     A   Statistical 

       Perspective. Willey. 



3.     Chambers,  R.  L.,  and  Skimmer,  C.  J.  (2003)  Analysis  of  Survey 

       Data. Wiley. 



4.     Chaudhary, A., and Stemger, H. (2005), Survey sampling theory and 

       methods. Chapman & Hall. 

5.     Cochran,  W.G.  (1977),  “Sampling  Techniques”,  3rd   ed,  John  Wiley 

       and Sons,          New York. 



6.     Ferguson, T.S. (1996), “A Course in large  Sample theory, Chapman 

       & Hall, London. 



7.     Kish, L. (1992). “Survey Sampling”, John Wiley, New York. 



8.     Paduri   S.  R.   S.   Rao   (2000)   Sampling     Methodologies     with 

       Applications, Chapman & Hall 



9.    Raj, D. (1971) “Design of Sample Survey”. McGraw Hill, New York. 



10.      Raj,  D.  &  Chandhok,  P.  (1998),  “Sample  Survey  Theory”.  Narosa 

       Publishing House, New Delhi. 



11.    Singh,  R.  and  Singh  N,  (1996),  “Elements  of  Survey  Sampling”, 

       Kulwar Academic Publisher, Dodrecht. 



12.    Sukhatme, P.V,  Sukhatme, B.,  Sukhatme, S.,  and  Asok, A. (1985), 

       “Sampling Theory of Survey with Application”. Iowa State University 

       Press 



STAT- 307:       Regression Analysis 



General  linear  model  and  its  assumptions,  Least  squares  estimators, 

Maximum Likelihood Estimator, tests of significance for regression model 

and    regression    parameters.    Confidence     intervals   for   regression 

parameters, Test of linearity of regression,  Use of extraneous information in  linear  regression  model.  Residual  analysis,     Detection  and  study  of 

outliers,   Polynomial    regression,    orthogonal     polynomial,    orthogonal 

regression analysis, Specification of models 



Pre-Requisite:             STAT-203 



Recommended Books: 



1.     Baltagi, B. H. (1999). “Econometrics”, 2nd Edition, Springer Varlog. 

2.     Johnston,  J.  and  Di.  Nardo,  J.,  (1997).  “Econometric  Method”,  4th 

       Edition, McGraw-Hill, New York. 



3.      Maddela, G.S. (1977). “Econometrics”, McGraw Hill. New York. 



4.     Searle, S. R. (1971), “Linear Models”, John Wiley, New York. 



5.     Yan, X. and Zu, X. G. (2009) Linear Regression Analysis: Theory & 

       Computing. World Scientific Publications. 



6.     Wonnacott, T.H. and Wonnacott R.J. (1998). “Econometrics”, John 



       Wiley, New -York. 



STAT- 305:        Design and Analysis of Experiments-I 



Principles   of   Design   of   Experiments,   Analysis    of   variance   and   its 

assumptions, Cochran theorem, Fixed, random and mixed effect models, 



Completely   Randomized,       Randomized   Complete   Block,   Latin   square, 

Graeco-Latin     square   and    cross-over   designs,    Missing   observations, 

Relative  efficiency  of  designs,   Estimation  of  mean  squares  and  their 

expectations, Multiple Comparisons tests 



Analysis of covariance in CR, RCB designs,  Estimation of missing values 

in analysis of covariance. 



Effect of violation of assumptions and transformations 



Pre-Requisite:             STAT-203 



Recommended Books: 



1.        Boniface,  D.R.  (1995).  “Experiment  Design  &  Statistical  Methods”, 

       Chapman & Hall. 



2.     Cochran, W.G. and Cox, G.M. (1992). “Experimental Design”, John 

       Wiley, New York. 3.     Clarke,  G.M.  (1994).  “Statistics  &  Experimental  Design”.  Edward 

       Arnold. 

4.     Clarke, G.M., and Kempton, R.E. (1997), “Introduction to the Design 

       & Analysis of Experiments”, Edward Arnold. 



5.     Das,    M.N.and     Geri,   N.C,   (1986).    “Design    and    Analysis    of 

       Experiments”, John Wiley,  New York. 



6.     Gomez,  K.A.,  and  Gomez,  A.A.  (1984).“Statistical  Procedures  for 

       Agricultural Research”, 2nd  Edition, John Wiley, New York. 



7.     Harold, R. L (1992). “Analysis of Variance in Experimental Design” . 

       Springer Verlage 



8.     Hicks, C.R. (1982). “Fundamental Concepts in Design and Analysis 

       of Experiments” Saunders 



9.     Hunter,  B.  and  Hunter,  W.  G.  (2005)  Statistics  for  Experimenters: 

       Design, Innovation and Discovery. Wiley. 



10.    Maxwell,  S.E.  and  Delaney,  H.D.  (1990).  “Designing  Experiments 

       and  Analysis  of  Data”.  A  model  comparison  perspective.  Belment 

       and Wadeson. 



11.    Mead,     R.   (1988).   “The    Design    of  Experiments”.      Cambridge 

       University Press, Cambridge. 



12.    Montgomery, D. C., Design and analysis of experiments, Edition: 7th 

       ed. Publisher: New Jersey : John Wiley, 2009 



13.    Myers,  R.H.  and  Montgomery,  D.C.  (1995).  “Response  Surface 

       Methodology; Process  & Product Optimization Using Design”, John 

       Wiley. 



14.    Steel, Robert, G. D., Terrie James H., and Dickey David A. (1997). 

       “Principles and Procedures of Statistics: A Biometrical Approach” 3rd 

       Edition, McGraw-Hill, New York. 



STAT- 310:         Non-Parametric Methods 



Chi-Square Procedures: Chi-Square Goodness of fit Test, Chi-Square test 

of  independence,  Location  estimates  for  single  sample:  The  sign  test, 

modified sign test, Wilcoxon signed rank test, confidence interval based on 

these tests. Runs test for randomness. 



Distribution tests and rank transformation, Kolmogrov’s test, Lilliefor’s test 

and   Shapiro-Wilks   test   for   normality.   Tests   and   estimation   for   two 

independent samples; the median test, Wilcoxon Mann – Whitney test. The 

Siegel – Tukey test, the squared rank test for variance, Smirnov test, Tests 

for   paired   samples,    Kruskal   –  Wallis   test,   Friedman   test,   multiple 

comparison  with  the  Friedman  test,  Cochran’s  test  for  binary  responses Spearman’s      rank    correlation   coefficient,   Kendall’s    rank   correlation 

coefficient. Theil’s regression method 



Pre-Requisite:              STAT-202 



Recommended Books: 

1.     Conover, W.J. (1999), Practical Nonparametric Statistics, 3rd  Edition, 

       John Wiley and Sons, New York 

2.     Gibbons, J.D. and Chakraborti, S. (1992), Nonparametric Statistical 

       Inference, Marcel Decker, New York. 

3.     Lehman,  E.L.  (1973), Nonparametric  Statistical  Methods,  based  on 

       Ranks, Holden-Day San Francesco 

4.     Maritz, J.S. (1995). Distribution-Free Statistical Methods, Chapman & 

       Hall London 

5.     Sprint,  P.  (2007).  Applied  Nonparametric  Statistical  Methods,  4th 

       edition, Chapman & Hall London 



STAT- 302:         Probability and Probability Distributions-II 



Uniform, Lognormal, Exponential, Gamma, Laplace, Rayleigh, Weibell with 

moments and cummulants; Distributions of functions of random variables: 

Chi-square, t and F distributions, their derivations and properties. Central 

limit and Chebyshev's theorems and other inequalities, Weak and Strong 

Laws of large numbers and their applications, Order statistics, Distributions 

of rth and sth  order statistics, Bivariate Normal distribution. 



Pre-Requisite: STAT-301 



Recommended Books: 



1.     Dekking, F. M., Kraaikamp, C., and Lopuhaae, H. P., and Meester, 

       L.  E.  (2005)  A  Modern  Introduction  to  Probability  and      Statistics. 

       Springer. 

2.     Fridett,  B.  &  Gray,  L.  (1997).  “A  Modern  Approach  to  Probability 

       Theory” Birkhallser, Boston. 



3.        Freund,  J.  E.  (1997).  “Mathematical  Statistics”,  Prentice  Hall,  New 

       Jersey. 



4.     Haq, M. (1984). “Foundation of Probability and Statistics”, Tahir sons, 

       Urdu Bazar, Karachi. 



5.     Hirai, A.S. (1998), “A Course in Mathematical Statistics”,  Ilmi Kutab 

       Khana,      Lahore. 



6.     Hogg,  R.M.  and  Craig,  A.T.  (1995),  “Introduction  to  Mathematical 

       Statistics”. Prentice Hall, Engle wood Cliffs, New Jersey. 



                                         24 


----------------------- Page 25-----------------------

7.     Khan,  M.  K.,  (1996).  “Probability  with  Applications”,  Maktiba  Ilmi, 

       Lahore. 

8.     Mood, A.M, Graybill, F.A. and Boss, D.C. (1997), “Introduction to the 

       Theory of Statistics”, McGraw-Hill, New York. 



9.     Stirzaker, D. (1999). “Probability and Random Variables”. Cambridge 

       University Press, Cambridge. 



10.    Stuart,  A.  and  Ord,  J  .K.  Kendall’s   (1998),   “Advanced  Theory  of 

       Statistics”, Vol. I, Charles Griffin, London. 



STAT- 304:         Sampling Techniques-II 



Cluster   Sampling,     Sub    sampling,    PPS-Sampling,       Double    Sampling, 

Multistage    and    Multiphase     sampling,     Thomson      Hurwitz     estimator, 

Comparison of different sample designs; non-response, their sources and 

bias,  Randomized  response,  Critical  study  of  National  sample  surveys 

conducted     in   Pakistan:    Census     of   Agriculture    Pakistan,    Pakistan 

Demographic Survey (PDS) and National Population and Housing Census 



Note:   Practical’s  of  this  course  shall  include  visits  of  the  students  to 

various  national  statistical  organizations  and  a  report  submitted  to  this 

effect. 



Pre-Requisite:              STAT-303 



Recommended Books: 



1.     Brewer,    K.   R.   &   Hanif,   M.   (1983).   Sampling     with   Unequal 

       Probabilities.  Lecture  Notes  in  Statistics  Series,  No.  15,  Springer 

       Verlag. 



2.     Bethelem,     J.   (2009)    Applied    Survey    Methods:      A   Statistical 

       Perspective. Wiley. 



3.     Chambers,  R.  L.,  and  Skimmer,  C.  J.  (2003)  Analysis  of  Survey 

       Data.  Wiley. 



4.     Chaudhary, A., and Stemger, H. (2005), Survey sampling theory and 

       methods. Chapman & Hall. 



5.     Cochran,  W.G.  (1977),  “Sampling  Techniques”,           John  Wiley  and 

       Sons, 3rd  ed, New York. 



6.     Des Raj, (1971), Design of Sample Survey. McGraw-Hill, New York. 



7.     Des  Raj  &  Chandhok,  P.  (1998),  “Sample  Survey  Theory”.  Narosa 

       Publishing House, New Delhi. 8.     Ferguson,   T.S.   (1996),   “A   Course   in   Large   Sample   Theory” , 

       Chapman & Hall, London. 



9.     Hansen, M. H., Hurwitz, W. N. & Madow, W.G. (1952). 



10.    Kish, L. (1992), “Survey Sampling”, John Wiley, New York. 

11.    Singh,  R.  and  Singh  N,  (1996),  “Elements  of  Survey  Sampling”, 

       Kulwar, Dodrecht. 



12.    Sukhatme, P.V, Sukhatme, B., Sukhatme, S., and Asok, A. (1985), 

       “Sampling Theory of Survey with Application”. Iowa State University 

       Press. 



13.    Sukhatme, P.V, Sukhatme, B., Sukhatme, S., and Asok, A. (1985), 

       “Sampling Theory of Survey with Application”. Iowa State University 

       Press. 



14.    Various publications of Pakistan Bureau of Statistics (PBS). 



15.    Hansen, M. H., Hurwitz, W. N., and Madow, W. G. (1993) Sampling 

       Survey Methods and Theory, Vol. 1 and II, Wiley. 



STAT- 308:        Econometrics 



Introduction to econometrics, Problems of autocorrelation, multicollinearity, 

heteroscedasticity and their solution; Ridge regression,  Lagged variables, 

Dummy  variables,  Errors  in  Variables,  Instrumental  variables,  System  of 

simultaneous  linear  equations,  Identification-Estimation  method,  indirect 

and  two-stage  least  squares  methods,  restricted  least  squares.  Test  of 

identifying  restrictions;  Estimation  with  stochastic  regressor,  generalized 

least squares estimators. 



Pre-Requisite:             STAT-307 



Recommended Books: 



1.     Baltagi, B. H. (1999). “Econometrics”, 2nd Edition, Springer Varlog. 



2.     Draper,  N.R.  and  Smith,  H.  (2004).  “Applied  Regression  Analysis” , 

       John Wiley, New York. 



3.     Gujrati, D. (2004). “Basic Econometrics”, John Wiley, New York. 



4.     Guttmann,  I.  (1980);  “Linear  Models:  An  Introduction”,  John  Wiley, 

       New York. 

5.     Johnston,  J.  and  Di.  Nardo,  J.,  (1997).  “Econometric  Method”,  4th 

       Edition, McGraw Hill, New York. 



6.     Koutsoyiannis, A. (1980), “Theory of Econometrics”, Macmillan. 
7.        Montgomery,  D.C.,  and  Peck  E.A.  (1992).  “Introduction  to  Linear 

       Regression  Analysis” , 2nd Edition. John Wiley  and  sons Inc. New 

       York 



8.     Wonnacot,  T.H.  and  Wonnacot  R.J.  (1998).  “Econometrics”,  John 

       Wiley, New York 



STAT- 306:         Design and Analysis of Experiments-II 



                             k   k 

Factorial Experiments: 2 , 3      series and mixed level factorial experiments 

and their analyses. 



Confounding  in  factorial  experiments,  Complete  and  partial  confounding, 

Confounding  in  Fractional  replications.  Split-plot,  split-split  plot,  strip  plot 

and  nested  designs.  Missing  observations  in  Split  plot  design.  Response 

surface designs. 



Incomplete  block  designs:  BIBD        - Lattice  designs,  lattice  square  and 

Youden squares, PBIBD with recovery of intra-block information. 



Pre-Requisite:              STAT-305 



Recommended Books: 



1.     Boniface,  D.R.  (1995).  Experimental  Design  &  Statistical  Methods , 

       Chapman & Hall. 



2.     Clarke,  G.M.  (1994).  “Statistics  &  Experimental  Design”.  Edward 

       Arnold. 



3.     Clarke, G.M., and Kempton, R.E. (1997), “Introduction to the Design 

       & Analysis of Experiments”, Edward Arnold. 



4.     Das,    M.N.and     Giri,   N.C,   (1986).    “Design     and    Analysis    of 

       Experiments”, John Wiley, New York. 



5.     Gomez,  K.A.,  and  Gomez,  A.A.  (1984).  “Statistical  Procedures  for 

       Agricultural Research”, 2nd  Edition, John Wiley, New York. 



6.     Giesbrecht,  F.  G.,  Gompertz,  M.  L.  (2004)  Planning,  Construction, 

       and Statistical Analysis of Comparative Experiments. Wiley. 



7.     Harold, R. L (1992). “Analysis of Variance in Experimental Design” . 

       Springer Verlag: 



8.     Hicks, C.R. (1982). “Fundamental Concepts in Design and Analysis 

       of Experiments”; Saunders 



9.     Maxwell, S.E. and Delaney, H.D. (1990). Designing Experiments and 

       Analysis  of  Data.  A  Model  Comparison  Perspective .  Belmont  and 

       Wadeson. 
10.    Mead, R., Gilmour, S., and Mead, A. (1990) Statistical Principles for 

       the  design  of      experiments:  Applications  to  real  experiments. 

       Cambridge University Press, Cambridge. 



11.     Montgomery,  D.C.  (2000).  “Design  and  Analysis  of  Experiments”, 

       John Wiley, New York 

12.    Myers,  R.H.  and  Montgomery,  D.C.  (1995).  “Response  Surface 

       Methodology;  Process & Product Optimization Using  Design”, John 

       Wiley 



13.   Steel, G. D., Terrie, and Dickey A. (1997). “Principles and Procedures 

       of Statistics: A Biometrical Approach ” 3rd      Edition, McGraw-Hill, New 

       York 



STAT- 311:         Population Studies 



Basic  concepts  of  demography,         Sources  of  demographic  data:    The 

population and housing census, Registration of vital events. Demographic 

surveys, Components of population growth, composition of population and 

vital events, Types and sources of errors, Data quality testing procedures, 

testing  the  accuracy  of  age  and  sex  distribution,      Fertility  and  mortality 

measures, Estimation from incomplete Data 



Construction  of  complete  and  abridged  life  tables,  Different  types  of  life 

tables, Graphs of l , q    and e , Description and uses of life table columns. 

                     x   x       x 



Stationary population models, Population estimates and projections, Inter- 

censual    estimates,    Population     projections    through    various   methods. 

Theory of demographic transition, Stable and stationary population models, 

their  applications  and  uses,  Malthusian  and  post  Malthusian  theories  of 

growth, Consequences of world population growth & population explosion; 

State  of  Population  in  Pakistan,  Development  of  demographic  profile  in 

Pakistan,     Recent      demographic       parameters.      Current     and    future 

demographic activities in Pakistan 



Recommended Books 



1.     Bogue,  D.J.  Arriagu,  E.E.,  Anderson,  D.L.  (1993),  “Readings  in 

       Population Research Methodology”, Vol. I-VIII, United Nations Fund; 

       Social Development Centre, Chicago. 



2.     Hinde, A., (1998). “Demographic Method”, Arnold New York. 



3.     Impagliazo,     J.  (1993),    Deterministic    Aspects     of  Mathematical 

       Demography, Springer Verlag New York. 



4.    Jay Weinstein, Vijayan, K. Pillai, (2001) “Demography: The Science of 

       Population”. Allyn & Bacon.1. 
5.     Keyfitz,  N.  (1983)  “Applied  Mathematical  Demography”,        Springer 

       Verlag N.Y. 



6.     Palmore, J.A; Gardner, R.W. (1994), “Measuring Mortality Increase”; 

       East West Centre, Honolulu. 



7.      Pollard,  A.H.,  Yousaf,  F  &  Pollard,  G.M.  (1982),    “Demographic 

       Techniques”, Pergamon Press, Sydney. 

8.     Rukanuddin   A.R.   and   Farooqi,   M.N.I..,   (1988),   “The   State   of 

       Population in Pakistan –  1987”, NIPS, Islamabad. 



9.     Govt.  of  Pakistan  (1998),  National,  Provincial  and  District  census 

       reports   and   other   supplementary   reports   with   respect   to   1998 

       census; PCO, Islamabad. 



10.    Pakistan Demographic Survey (2007), Govt. of Pakistan. 



11.    Publications of population census organizations. 



12.    United Nations (1990), “World Population Monitoring 1989”, UNFPA. 



13.   United Nations (1998), “World Population Assessment”, UNFPA; New 

       York. 



14.   United Nations (1996), “Added years of Life in Asia” , ESCAP; U.N., 

       Thailand. 



15.    Haupt,  A.,  Kane,  T.  T.,  and  Haub,  C.  (2011)  PRB’s  Population 

       Handbook. 



STAT- 401:        Statistical Inference-I 



Estimation    of  Parameters,     Properties    of  Estimators:    unbiasedness, 

consistency, sufficiency, efficiency, Invariance, completeness. Cramer-Rao 

inequality,  Rao-Blackwell and  Lehmann  -  Scheffe  Theorems,  Methods  of 

Estimation:  Moments,  Maximum  likelihood,  least-squares,  minimum  Chi- 

square and Bayes’ method. 



Pre-Requisite:             STAT-302 



Recommended Books: 



1.     Bickel, P.J., and Docksum, K.A. (2005), Mathematical Statistics, Vol 

       I, Prentice Hall, N.J., 2nd  ed. 



2.     Hogg,  R.V.  and  Craig,  A.T.  (1996).  “Introduction  to  Mathematical 

       Statistics”. Prentice Hall, New Jersey. 



3.     Lindgren, B.W. (1998). “Statistical Theory”. Chapman and Hall, New 

       York. 
4.     Mood, A.M., Graybill, F.A. and Boss, D.C. (1997). “Introduction to the 

       Theory of Statistics”. McGraw Hill, New York. 



5.     Rao, C.R., (2009). “Linear Statistical Inference and its Applications”, 

       John Wiley, New York. 



6.     Rohatgi,    V.   K.   (1984)     Statistical  Inference.    Courier    Dover 

       Publications. 



7.     Stuart,  A.  and  Ord,  J.K.  (2009).   Kendall’s’  “Advanced  Theory  of 

       Statistics” Vol. II. Charles Griffin, London. 



8.     Zacks, S. (1973), “Parametric Statistical Inference”, John Wiley, New 

       York. 



STAT- 403:         Multivariate Analysis 



Introduction  to  Multivariate  data  analysis,  Basics  of  matrix  and  vector 

algebra,  Geometry  of  vectors  and  sample,  Expectation  of  sample  mean, 

covariance  matrix,  linear  combination  of  variables,  Generalized  variance, 

Multivariate   Normal   Distribution:   Multivariate   Normal   density   and   its 

properties,  Sampling  distribution  of  sample  mean  vector  and  covariance 

matrix   including    their  large   sample    behavior.    Assessing     normality, 

transformation to make non-normal data to normal, Outliers, Hotelling’s T2 

and  likelihood  ratio  tests,  Inferences  about  mean  vector(s),  Confidence 

regions and simultaneous comparisons of component means, Multivariate 

Linear Regression. 



Principal   components      analysis,    Factor   Analysis,   Discrimination     and 

Classification, Cluster Analysis 



Recommended Books: 



1.     Afifi,  A.  A.  and  Clark  Virginia  (1984).    Computer  Aided  Multivariate 

       Analysis, Lifetime learning publications, Belmont California. 



2.     Anderson,  T.W.  (2003).  An  Introduction  to  Multivariate  Statistical 

       Analysis, John Wiley, New York. 



3.     Chatfield,  C.  and  Collins,  A.J.  (1980).    Introduction  to  Multivariate 

       Analysis, Chapman and Hall, London. 



4.     Everett, B.J. (1974). Cluster Analysis, McGraw-Hill, New York. 



5.     Flurry  B.  (1997)  A  First  Course  in  Multivariate  Statistics,  Springer 

       Valerg, New York. 



6.     Hair,  J.F.,  Anderson  R.E.,  Jatham,  R.L.and  Black  W.C.,  (1998). 

       Multivariate Data Analysis, 5th  ed. Pearson Education, Re print 2005, 

       Asia edition. 
7.     Johnson,  R.A.  and  Wichern,  D.W.  Applied  Multivariate  Statistical 

       Analysis (6th ed.). Prentice Hall. London. 



8.     Joseph  F.  Hair  Jr, William  C.  Black , Barry  J.  Babin        ,Rolph  E. 

       Anderson (2009).  Multivariate  Data  Analysis  (7th  Edition),  Pearson 

       education Asia Edition. 



9.     Manly, B.F.J. (1994).  Multivariate Statistical Methods, A Primer 2nd 

       Edition, Chapman and Hall, London. 

10.    Mardia,   K.V.,   Kent,   J.T.   and   Bibby,   J.M.   (1979).      Multivariate 

       Analysis, Academic Press, London. 



11.    Morrison.  F.  (1990).  Multivariate  Statistical  Methods,  McGraw-Hill, 

       New York. 



12.    Raykov,  T.  and  Marcoulides,  G.  A.  (2008)  Introduction  to  Applied 

       Multivariate Analysis. Tylor & Francis. 



13.    Rechner, A. C. (2002) Methods of Multivariate Analysis. Wiley. 



14.    Sharma, S. (1996), Applied Multivariate Techniques, John Wiley and 

       Sons, New York. 



15.    Tabachnick,     B.G    and    Fidell,  L.S.   (1996),    Using    Multivariate 

       Statistics, 3rd  ed. Harper Collins College Publishers. 



STAT- 402:         Statistical Inference-II 



Interval   Estimation:   Pivotal   and   other   methods   of   finding   confidence 

interval, confidence interval in large samples, shortest confidence interval, 

optimum confidence interval. Bayes’ Interval estimation 



Tests  of  Hypotheses:  Simple  and  composite  hypotheses,  critical  regions. 

Neyman-Pearson Lemma, power functions, uniformly most powerful tests. 

Deriving tests of Hypothesis concerning parameters in normal, exponential, 

gamma  and  uniform       distributions,  Randomized  Tests,       Unbiased  tests, 

Likelihood  ratio  tests  and  their  asymptotic  properties.  Sequential  Tests: 

SPRT and its properties, A.S.N. and O.C. functions. 



Pre-Requisite:              STAT-401 



Recommended Books: 



1.     Hogg,  R.V.  and  Craig,  A.T.  (1996).  “Introduction  to  Mathematical 

       Statistics”. Prentice Hall, New Jersey. 



2.     Hirai,  A.  S.  (2012)  Estimation  of  Parameters.  Ilmi  Kitab  Khana 

         Lahore. 



                                          31 


----------------------- Page 32-----------------------

3.     Lehman,  E.L.  (2008).  “Testing  Statistical  Hypotheses”.  Springler  - 

       Volga, New York. 



4.     Lindgren, B.W. (1998). “Statistical Theory”. Chapman and Hall, New 

       York. 



5.     Mood,  A.M.  Gray  Bill,  F.A.  and  Boss,  D.C.  (1997).  “Introduction  to 

       the Theory of Statistics”. McGraw Hill, New York. 



6.     Rao, C.R., (2009). “Linear Statistical Inference and its Applications”, 

       John Wiley, New York. 

7.     Stuart,  A  and  Ord,  J.K.  (2009).  Kendall’s’  “Advanced  Theory  of 

       Statistics” Vol. II. Charles Griffin, London. 



8.     Welish, A. H. (2011) Aspects of Statistical Inference. Wiley. 



9.     Zacks, S. (1973), “Parametric Statistical Inference”, John Wiley, New 

       York. 



STAT-  422:                RESEARCH PROJECT / INTERNSHIP 



                                        32 


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                          ELECTIVE COURSES 



STAT- 405:        Research Methodology 



Definition of Research, Types of Research: Selection of Problem, Search 

of  References,  Formation  of  Hypothesis  and  Procedure  for  its  Testing, 

Research Design, Planning of Experiments to Test Hypothesis Objectivity, 

Principals  of  Experimental  Design,  Steps  in  Experimentation,  Designing 

Questionnaire, Collection of Data, Data Analysis to Determine, Functional 

Relationship  Between  Variables,  Levels  of  Significance,  Interpretation  of 

Results, Components of Scientific Reports and Various Methods of Data, 

Presentation,  Preparation  of  Scientific  Reports,  Publication  Procedures. 

Qualitative Research: content analysis. 



PRACTICAL:           Survey  of  Literature  on  a  Given  Topic,  Collection  of 

References  from  Various  Sources.  Collection  of  Primary  and  Secondary 

Data,   Arrangement   of   Primary   and   Secondary   Data,   Preparation   of 

Scientific Report for Publication, if Possible 



Pre-Requisite:             STAT-304 



Recommended Books: 



1.     Gimbaled, J. and W.S. Acuter (1988) “MLA handbook for Writers of 

       Research  Papers”,  McGraw  the      Modern  Language  Association  of 

       America. 



2.     Hashmi,     N.   (1989)    “Style   Manual    of   Technical     Writings”, 

       USAID/NARC, Islamabad. 



STAT-406:         Operations Research 



History   and   definition   of   Operation   Research,  Introduction   to   linear 

programming,     Formulation    of  LP   model,    Graphical   solution   of  two 

variables,  Standard  Form,  Simplex  method,        Duality  theory;  Sensitivity 

Analysis,   Primal   and   dual   form, Transportation   Problem,   Assignment 

problem.   Network   Analysis,   PERT/CPM   techniques,       Queuing   Models, 

Inventory models, Dynamic programming and simulation models 



Recommended Books: 



1.     Bazarra,   N.M.,   Jarvis   J.J.  and   Sherali,   H.D.   (1990)   “Linear 

       Programming and Network Flows”, John Wiley & Sons, 2nd  ed. 



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----------------------- Page 34-----------------------

2.     Bronson,  R.  (1983).  “Operations  Research       –   Schaums’  Outline 

       Series” – McGraw-Hill. 

3.     Gupta, P.K. & Hira, D.S. (2008). “Operations Research”. (7th ed.) S. 

       Chand & Co., New Delhi. 



4.     Hillier, F.S. and Lieberman G. J. (2005). “Introduction to Operations 

       Research”, (8th ed.)Holden Day. 



5.     Ravindran,  A.,  Philips,  D.J  and  Silberg,  J.J.  (2007).  “Operations 

       Research: Principles and Practice” (2nd ed.) John Wiley. 



6.     Taha, H.A. (2002) Operations Research. Macmillan. London 



STAT- 407:        Stochastic Processes 



Introduction,   Generating     Functions,   Laplace    Transforms,     Difference 

Equations,   Differential-Difference   Equations,   Introduction   to   Stochastic 

Processes. The Random Walk in one and two Dimensions, The Classical 

Gambler’s Ruin Problem, Expected Duration of the Game 



Markov Chains: Definition. Higher Transition Probabilities, Classification of 

States and Chains, Markov processes with Discrete State Space, Poisson 

Process and its Generalization, Pure Birth and Death Processes, Markov 

Processes  with  Discrete  State  Space  (Continuous  Time  Markov  Chains), 

Markov Processes with Continuous State Space. Introduction to Brownian 

motion 



Recommended Books 



1.     Cox,   D.R.and    Miller  H.D.   (1984).   “The   Theory    of  Stochastic 

       Processes”, Chapman and Hall, London. 



2.     Grimmet   G.   and   Stirzaker   D.   (2001):   Probability   and   Random 

       Processes, Oxford University Press. 



3.     Hole,  P.G.,  Port,  S.  and  Stone,  C.L.  (1984).  “An  Introduction  to 

       Stochastic Process”, John Wiley, New York. 

4.     Karlin,  S.A.  and  Taylor  H.M.  (1984).  “A  first  course  in  Stochastic 

       Process”, Academic Press London. 



5.     Medhi, J. (1982), “Stochastic Processes”, Wiley Eastern Ltd. 



6.     Ross, S. M. (2006). “Stochastic Process”, John Wiley, New York. 



7.     Srinivasin,  S.K.  and  Mehta,  K.M.  (1988).   “Stochastic  Processes”. 

       Tata McGraw-Hill. 



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----------------------- Page 35-----------------------

STAT- 408:         Reliability Theory 



Basic  concepts  of  reliability,  Structural  reliability, Life  time  distributions 

(Failure models): Hazard rate; Gamma, Weibull, Gumball, Log-Normal and 

Inverse  Gaussian  Distribution.  Stochastic  fatigue-rate  models,  Point  and 

interval estimation,  Fatigue-life model 



Testing reliability hypothesis, Monte-Carlo simulations, distribution-free and 

Bayes’   methods   in   reliability,   System   reliability;   series   and   parallel 

systems,    Failure   models,   (k-out-of-m)   New-better-than   used   models. 

Inferences for these models,  Accelerated life testing 



Recommended Books: 



1.     Achintya     Haldar,     Sankaran      Mahadevan        (2000).     Reliability 

       Assessment Using Stochastic Finite Element Analysis”. 



2.     Crowder, M.J. (1994). “Statistical Analysis of Reliability Data”. 



3.     Gertsbakh,     I.B.  (1989).    “Statistical  Reliability  Theory”.    Marcel 

       Decker. New York. 



4.     Gertsbakh,  I.  Reliability  theory  :  with  applications  to  preventive 

       maintenance Publisher: New Delhi : Springer, 2009 



5.     Lawless, J.F. “Statistical Model and Methods for Lifetime Data”.(2nd 

       ed.) 



6.     Lee, J. Bain, Bain Bain, (1991). “Statistical Analysis of Reliability and 

       Life-Testing Models”. 



7.     Mann,  N.R.,  Scheefer,  R.E.  and  Singapoor  walla,  N.D.  (1974). 

       Methods for Statistical Analysis of Reliability , John Wiley & Sons. 



STAT- 409:         Time Series Analysis 



Time  series  analysis:  concepts,  Stochastic  Process,  Stationary  Time- 

Series,   Exponential   smoothing   techniques,   auto-correlation   and   auto- 

covariance,   estimation   of    auto-correlation   function   (ACF)   and   Partial 

autocorrelation    function    (PACF)     and   standard     errors,  Periodogram, 

spectral density functions, comparison with ACF, Linear stationary models: 

Auto   Regressive   Moving   Average   (ARMA)   and   mixed   models,   Non- 

stationary  models,  general  ARIMA  notation  and  models,  minimum  mean 

square forecasting. ARIMA Seasonal Models 



                                          35 


----------------------- Page 36-----------------------

Recommended Books: 



1.     Andy,  P,  West  M.  and  Harrison,  P.  J.  (1994).    Applied  Bayesian 

       Forecasting and Time Series Analysis, Chapman & Hall New York. 



2.     Bovas,    A.  and    Johannes,    L.  (1983),   Statistical  Methods     for 

       Forecasting, John Wiley. New York 

3.     Box,  G.E.P.  and  Jenkins,  G.M.,  and  Reinsel  G.  C.  (2008)  Time 

       Series Analysis: Forecasting and Control, San Francisco. 



4.     Brock  well  P.J.  and  Davis  R.A.  (1991).  Time  Series  Theory  and 

       Methods, Springer Verlag New York. 



5.     Chatfield,  C.  (1996). The  Analysis  of  Time  Series:  An  Introduction, 

       Chapman and Hall, London. 



6.     Chatfield  C.  (2003):  The  Analysis  of  Time  Series:  An  Introduction, 

       Taylor & Francis, NY, USA. 



7.     Cox,  D.  R.,  Hinckley  D.V.  and  Nielsen  O.E.B.  (1996).  Time  Series 

       Models  -  In  Econometrics,  finances  and  other  fields;  Chapman  & 

       Hall, London. 



8.     Diggle,   P.J.   (1990),  Time   Series:   A   Biostatistical   Introduction, 

       Clarendon Press, Oxford. 



9.     Jonathan D. C. and Kung-Sik C. (2008): Time Series Analysis with 

       Applications in R, Springer, USA. 



10.    Hamilton  J.  D.  (1994):  Time  Series  Analysis,  Princeton  University 

       Press, UK. 



11.    Harvey, A.C. (1990). Forecasting Structural Time Series Models and 

       the Calamander, Cambridge University Press, Cambridge. 



12.    Peter J. B and Richard A. D (2002): Introduction to Time Series and 

       Forecasting, Second Edition, Springer, USA. 



13.    Priestley, M.B. (1981) Spectral Analysis and Time Series, Academic 

       Press, London. 



STAT- 410:        Decision Theory 



The  nature  and    concept  of  loss  functions,   parameters,    decisions  and 

sample  spaces,  Risk  and  average  loss,  Admissibility  and  the  class  of 

admissible  decisions,    Minimax  principle   and   its  application  to  simple 

decision problems, linear and quadratic losses and their uses in problems 

of  estimation  and  testing  hypotheses.  Asymptotically  minimax  procedure, 

Prior   distributions   and   conjugate   priors,  Bayes’   decision   procedure. 

Admissibility of Bayes’ and minimax procedures. Game theory 



                                        36 


----------------------- Page 37-----------------------

Recommended Books: 



1.     Berger,   J.   O.   (1985).   “Statistical   Decision   Theory   &   Bayesian 

       Analysis”, Springer Verlag. 



2.     Blackwell,  D.  and  Graphic,  M.A.  (1966).  “Theory  of  Games  and 

       Statistical Decision”, John Wiley, New York. 



STAT- 411:         Robust Methods 



Introduction to Robustness, Objective function, M-estimator of location, E- 

estimator, R-estimator and W-estimator, Redescending M-estimator’s The 

Breakdown  point  of  Robust  estimator  Influence function.  M-estimator  for 

scale, Outliers and influential observations, Outliers in Regression analysis 



Recommended Books: 



1.     Hamper,  T.R.  Brochette,  E.M.  Rousseau,  P.J.  and  Satchel,  W.A. 

       (1986).   “Robust   Statistics”,   “The   approach   Based   on   Influence 

       functions”, John Wiley New York. 



2.     Hosmer D. W. and Lemeshow S. (2008): Applied Survival Analysis, 

       Wiley Interscience, USA. 



3.     Huber, P.J. (1981). “Robust Statistics”, John Wiley, New York. 



4.     Olive   D.   J.   (2007):   Applied   Robust   Statistics, Southern   Illinois 

       University Department of Mathematics. 



5.     Rousseau,  P.J.  and  Leroy,  A.M.  (1987).  “Robust  Regression  and 

       outlier detection”, John Wiley. New York. 



STAT- 412:         Official Statistics 



Official Statistics, Statistical system and international standards, set  up of 

national  statistical  organization  in  Pakistan,  its  role  in  development  of 

Statistics, working and publications. 



Sources  of  official  Statistics,   National  Database  Registration  Authority 

(NADRA)      and   its  role,  Economic      Statistics  producers,     International 

classification and standards 



Use of Statistics in administration and planning Concepts and evaluation of 

GDP,  GNP,  NNP,  Balance          of  Trade  and  payments,      Measurement  of 

Income Distribution, Prices and price mechanisms. Deflation and Inflation 

of series, Industrial quantum index, National sample surveys and censuses 

conducted in Pakistan. 



                                         37 


----------------------- Page 38-----------------------

Note:  Visit  of  major  Statistical  Organizations  should  be  a  part  of  the 

course.  Alternatively,  the  department  may  invite  experts  from  various 

statistical organizations. 



Recommended Books: 



1.     Hansen  M.H.  (1980).  “Progress  and  Problems  in  Survey  Methods 

       and Theory”. IIIustrated by the work of U.S. Bureau of the Census, 

       U.S. Department of Commerce; A Monograph. 

2.     NIPA  (1962)  “Administrative  uses  of  Statistics” ,  NIPA  Res.  Sr.No.2 

       Karachi. 



3.     Statistical  Institute  for  Asia  &  Pacific  SIAP  (1984).  “ Training  of 

       Trainers  in  Statistical  Operations  and  Procedures” Part-I,  II  UNDP, 

       Tokyo. 



4.     Statistics  Division  (1979).  “Retrospect,  Perspective  and  Prospect”, 

       Islamabad. 



5.     Statistics   Division,   “Activity  Report”    (1988-89).Government        of 

       Pakistan, Islamabad. 



6.     Various  Publications  of  PBS,  State  Bank  of  Pakistan,  Ministry  of 

       Finance, etc. 



7.     Zarkovich   S.S.   (1966)   “Quality   of   Statistical   Data,   Food   and 

       Agricultural Organization”, The U.N. Rome. 



8.     Statistics Reorganization Act 2011 



STAT- 413:        Survival Analysis 



Special  features  of  Survival  data:  Patient  time  and  study  time,  Survival 

function and hazard function, Time dependent and censored survival data. 

Nonparametric      procedures:     Estimation    of  Survival   function,   hazard 

function, median and percentiles of Survival times. Confidence interval and 

comparison  of  group;  stratified  and  log-rank  tests  for  trend,  Modeling  of 

Survival data; Hazard function modeling; its tests and confidence interval, 

The Weibull  model  for  survival  data,  Exploratory data  analysis  and  other 

models,  Sample  size  requirement  for  survival  study,  Use  of  software  for 

Survival analysis 



Recommended Books: 



1.     Burkett, M. (1995). “Analyzing Survival Data from Clinical Trials and 

       Observational Studies”; John Wiley New York. 



2.     Collett,  D.  (1994).  “Modeling  Survival  Data  in  Medical  Research”. 

       Chapman & Hall, London. 



                                         38 


----------------------- Page 39-----------------------

3.     Cox,   DR.   and   Oakes,   D.   (1984).   “Analysis   of   Survival   Data” ; 

       Chapman & Hall London. 



4.     Eland Johnson, R. C. and Johnson N. L. (1989), “Survival Models & 

       Data Analysis”. John Wiley N.Y. 



5.     Lee,  E.T.  (1992).  “Statistical  Methods  for  Survival  Data  Analysis”; 

       John Wiley. N.Y. 



6.     Lee, E.T. (1997). “Applied Survival Analysis”, John Wiley and Sons, 

       New York. 

7.     Muller, R.G. and Xian Zhou (1996). “Survival Analysis with long-term 

       Survivors”, John Wiley. New York. 



8.     Parmer M.K.B. & Macklin D. (1995). “Survival Analysis: A Practical 

       Approach ”; John Wiley New York. 



9.     Turkey,  J.  (1987).  “Exploratory  Data  Analysis”,  John  Wiley,  New 

       York. 



STAT- 414:        Biostatistics 



Definition of Biostatistics, type of variables and observations in biological, 

health   and   medical   sciences,   Uniqueness   in   terms   of   behaviour   of 

variables  their  domain,  and  units;  Categorical,  numerical  and  censored 

data.  Populations,  Target  populations  and  sampled  Population:  Role  of 

sampling  in  biostatistics,  Size  of  samples  of  various  types  of  studies, 

Proportions,    rates    and    ratios;  incidence,    prevalence     and    odds. 

Distributional  behaviour  of  biological  variables  (Binomial,  Poisson  and 

Normal), Role of transformation for analysis of biological variables, Probit 

and Logit transformations and their analysis, p values, its importance and 

role, Confidence Interval in simple and composite hypothesis testing 



Recommended Books: 



1.     Alfassi Z. B., Boger, Z. and Ronen, Y. (2005):  Statistical Treatment 

       of Analytical Data, Blackwell Science, USA. 



2.     Altman,   G.   (1991).   “Practical   Statistics   for   Medical Research”. 

       Chapman & Hall, London. 



3.     Ahmad, M., Ahmad, A., and Hanif, M. (2004) Manual of Statistics for 

       Medical Sciences. ISOSS Publications Lahore. 



4.     Daniel,  W.W.  (2010).  “Biostatistics:  A  Foundation  for  the  Health 

       Sciences”, 6th Edition, John Wiley, New York. 



5.     Diggle, J. P., Liang, Kung-Yee and Zeger, S. L. (1996). “Analysis of 

       Longitudinal Data”, Clarendon Press, Oxford. 



6.     Dunn,  G.  and  Everit,  B.  (1995).  “Clinical  Biostatistics”,    Edward 

       Arnold, London. 



                                        39 


----------------------- Page 40-----------------------

7.     Hanif  M.,  Munir  A.  and  Aftab  M.  A.  (2006):  Biostatistics  for  Health 

       Students with Manual on Software Applications, ISOSS Publication. 



8.     Harris, E. K. and Albert, A. (1991). “Survivorship Analysis for Clinical 

       Studies”. Marcel Decker, New York. 



9.     Lawless, J. F. (1982). Statistical Models and Methods for Life Time 

       Data. John Wiley, New York. 

10.    Lee, E.T. (1992). “Statistical Methods for Survival Data Analysis”, 2nd 

       Edition, John Wiley, New York. 



11.    Rosner, B. (2006). “Fundamentals of Biostatistics”, Duxbury Press. 



12.    Shoukri, M. M. & Pause, C. A. (1999). “Statistical Methods for Health 

       Sciences”. 2nd Edition, CRC Press, Florida. 



13.    Zar, J. (2000). “Biostatistical Analysis”, 5th Edition, John Wiley and 

       Sons. 



14.    Zolman,     J.F.  (1993).    “Biostatistics:  Experimental     Design     and 

       Statistical Inference”, Oxford University Press, New York. 



STAT- 415:         Data Mining 



Introduction to databases including simple and relational databases, data 

warehouses,  Review  of  classification  methods  from  multivariate  analysis; 

classification, decision trees: classification and regression trees. Clustering 

methods     from   both    statistical  and   data   mining    viewpoints;    vector 

quantization. Unsupervised learning from univariate and multivariate data; 

dimension   reduction   and   feature   selection.   Supervised   learning   from 

moderate to high dimensional input spaces; artificial neural networks and 

extensions  of  regression  models,  regression  trees.  Association  rules  and 

prediction; applications to electronic commerce 



Recommended Books 



1.     Benson  and  Smith,  S.J.  (1997).  “Data  Warehousing,  Data  Mining’, 

       and OLAP. McGraw-Hill. 



2.     Bramer M (2007): Principles of Data Mining. Springer-Verlag London 

       Limited UK. 



3.     Breiman,  L.  Friedman,  J.H.  Olshen,  R.A.  and  Stone,  C.J.  (1984). 

       “Classification and Regression Trees” Wadsworth and Brooks/Cole. 



4.     Han,  J.,  Kamber,  J.  Pei,  J.,  and  Burlington,  M.  A.  (2012)  Data 

       mining: concepts and techniques.  Haryana, India. 



5.     Han,   J.   and   Camber,   M.   (2000).   Data   Mining;   “Concepts   and 

       Techniques”. Morgan Gaufmann. 



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6.     Mitchell, T.M. (1997). “Machine Learning”. McGraw-Hill. 



7.     Rao  C.  R.,  Wegman  E.  J.  &  Solka  J.  L  (2005):         Handbook  of 

       Statistics, Vol. 24: Data mining and data visualization. Elsevier B.V., 

       North Holland. 



8.     Ripley,  B.D.  (1996).    “Pattern  Recognition  and  Neural  Networks”. 

       Cambridge University Press. 



9.     Suh,  S.  C.  (2012)  Practical  applications  of  data  mining.    Suh. 

       Publisher 



10.    Tan  P.,  Steinbach  M.  &  Kumar  V.  (2006):         Introduction  to  Data 

       Mining. Addison Wesley, New York . 



STAT- 416:         Actuarial Statistics-I 



Introduction  to  actuarial  Statistics,    Utility  theory,  insurance  and  utility 

theory,   models  for  individual  claims  and  their  sums,  survival  function, 

curate future lifetime, force of mortality 



Life table and its relation with survival function, examples, assumptions for 

fractional  ages,  some  analytical  laws  of  mortality,  select  and  ultimate 

tables. 



Multiple  life  functions,  joint  life  and  last  survivor  status,  insurance  and 

annuity  benefits  through  multiple  life  functions,  evaluation  for  special 

mortality laws 



Multiple decrement models, deterministic and random survivorship groups, 

associated  single  decrement  tables,  central  rates  of  multiple  decrement, 

net single premiums and their numerical evaluations. 



Distribution  of  aggregate  claims,  compound  Poisson  distribution  and  its 

applications 



Recommended Books: 



1.   Bowers, N.L. Gerber, H.U. Hickman, J.C. Jones, D.A. and Nesbitt, C.J. 

     (1997).  “Actuarial  Mathematics”,  Society  of  Actuarial,  Ithaca,  Illinois, 

     U.S.A 



2.   Dkkson, M. R., Hardy, H, Wates (2009) Actuarial Mathematics for Life 

     Contingent Risks. Cambridge. 



3.   Neill, A. (1977). “Life Contingencies”, Heineman. 



4.   Polard,   B.,   John,   H.   (1980)   Analysis   of   Mortality   and   Actuarial 

     Statistics. Faculty & Institute of Actuarial Sciences U.K. 



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5.   Spurgeon,  E.T.  (1972),  “Life  Contingencies”,  Cambridge  University 

     Press. 



STAT- 417:         Actuarial Statistics-II 



Principles of compound interest: Nominal and effective rates of interest and 

discount, force of interest and discount, compound interest, accumulation 

factor, continuous compounding. 



Life insurance: Insurance payable at the moment of death and at the end 

of   the   year   of   death-level   benefit   insurance,   endowment   insurance, 

deferred insurance and varying benefit insurance, recursions, commutation 

functions. 



Life  annuities:  Single  payment,  continuous  life  annuities,  discrete  life 

annuities,  life  annuities  with   monthly  payments,  commutation  functions, 

varying     annuities,    recursions,      complete      annuities-immediate        and 

apportionable annuities-due. 

Net premiums: Continuous and discrete premiums, true monthly payment 

premiums, apportionable premiums, commutation functions, accumulation 

type benefits. 



Payment   premiums,   apportionable   premiums,   commutation   functions, 

accumulation type benefits. 



Net  premium  reserves  :  Continuous  and  discrete  net  premium  reserve, 

reserves  on  a  semi-continuous  basis,  reserves  based  on  true            monthly 

premiums, reserves on  an apportionable or  discounted continuous basis, 

reserves   at   fractional   durations,   allocations   of   loss   to   policy   years, 

recursive  formulas  and  differential  equations  for  reserves,  commutation 

functions. 



Some  practical  considerations:  Premiums  that  include  expenses-general 

expenses types of expenses, per policy expenses. 



Claim  amount  distributions,  approximating  the  individual  model,  stop-loss 

insurance. 



Recommended Books: 



1.     Borowiak,  D.  S.,  Shapiro,  A.  F.  (2003)  Financial  and           Actuarial 

       Statistics: An Introduction. CRC Press. 



2.     Bowers,  N.L.  Gerber,  H.U.  Hickman,  J.C.  Jones,  D.A.  and  Nesbitt, 

       C.J.  (1986)  “Actuarial  Mathematics”,  Society  of  Actuaries,  Ithaca, 

       Illinois, U.S.A. Second Edition (1997). 



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3.     Corazza,  M.  and  Claudio,  P.  (2010)  Mathematical  and  Statistical 

       Methods for Actuarial Sciences and Finance. Springer. 



4.     Neill, A. (1977). “Life Contingencies”, Heinemann. 



5.     Spurgeon,  E.T.  (1972).  “Life  Contingencies”,  Cambridge  University 

       Press. 



STAT- 418:         Mathematical Modeling and Simulation 



Monte Carlo methods: Different methods of generating random numbers, 

generation of random variables, acceptance and rejection techniques from 

various   distributions.   Comparison   of   algorithms   to   generate   random 

variables, generating random variables from failure rates, 

Generation  from  multinomial  distribution  /  Monte  Carlo  integration,  Gibbs 

sampling and other resampling techniques, Variance reduction techniques: 

importance     sampling     for  integration,   control   variates   and    antithetic 

variables. 



Recommended Books: 



1.     Bernard  P  Autor  Zeigler,  Herbert  Praehofer,  Tag  Gon  Kim  (2000) 

       Theory of Modeling and Simulation 



2.     Daniel   P.   M,   Maynard   T.    (2006):   Mathematical   Modeling   and 

       Computer Simulation, Thomson Brooks/Cole 



3.     Fishman,  G.S.  (1996).  Monte  Carlo:        “Concepts,  Algorithms,  and 

       Applications”, (Springer). 



4.     Ripley, B.D. (1987) “Stochastic Simulations” ( Wiley) 



5.     Ross, S.M. (2002). “Simulation” ( Third Edition) (Academic) 



6.     Rubinstein, R.Y. (1981). “Simulation and the  Monte  Carlo  Method”, 

       (Wiley). 



7.     Velten,  K.  (2009):  Mathematical  modeling  and  simulation,  Wiley 

       VCH, Germany 



STAT- 419:         Categorical Data Analysis 



A  brief  history  of  categorical  data  analysis,  Principles  of  likelihood-based 

inference,  Sampling  distributions  for  contingency  tables,  Measures  of 

association  for  2x2  tables,  Testing  independence  in  contingency  tables, 

Exact inference for two-way tables, Inferences for three-way tables. 



Introduction   to   generalized   linear   models,   Logistic   regression,   Model 

building,  Alternative  link functions for  binary  outcome,  Diagnostics,  Exact 



                                         43 


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methods   and   conditional   logistic   regression,       Methods   for   analyzing 

matched case-control data, Multinomial response models for nominal data, 

Multinomial response models for ordinal data. 



Poisson regression model, Poisson regression for rates, Log linear models 

for contingency tables 



Recommended Books: 



1.     Alan Agresti (2012) Categorical Data Analysis (3rd  edition). Wiley. 



2.     Alan Agresti (2007) An Introduction to Categorical Data Analysis (2nd 

       edition). John Wiley & Sons. 



3.     Chap T. Le (1998) Applied Categorical Data Analysis. Wiley 



4.     Collett D. (2003) Modeling Binary Data. Champman and Hall/CRC. 



5.     Hosmer  D.  W.,  Lemeshow  S.  (2004)  Applied  Logistic  Regression. 

       John Wiley & Sons. 



6.     Lloyd C. J. (1999) Statistical Analysis of Categorical Data. Willey 



7.     Powers D. A., and Yu Xie (2008) Statistical Methods for Categorical 

       data analysis (2nd  edition). Emerald Group publishing. 



8.     Ronald  C.  (1997)  Log-linear  models  and  logistic  regression  (2nd 

       edition). Springer. 



9.     Simonoff J. S. (2003) Analyzing Categorical Data. Springer 



STAT- 422:         Bayesian Inference 



Conditional  Probability,  Prior  information,  Prior  distributions,  Methods  of 

elicitation   of   prior   distributions,   Posterior   distributions:   The   posterior 

means, medians (Bayes estimators under loss functions) and variances of 

univariate   and   bivariate   posterior   distributions,   Non-informative   priors: 

Methods  of  elicitation  of  non-informative  priors,  Bayesian  Hypotheses 

Testing: Bayes factor; The highest density region; Posterior probability of 

the hypothesis. 



Recommended Books: 



1.     Berger, J.O., Statistical Decision Theory and Bayesian Analysis (2nd 

       Ed.), New York, Springer Verlag (1985). 



2.     Bernardo, J. M. & Smith, A.F.M., Bayesian Theory, John Wiley, New 

       York (1994). 



3.     Box, G.E. P & Tiao, G. C. Bayesian Inference in Statistical Analysis, 

       Reading Addison-Wesley (1973). 



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4.     Introduction to Bayesian Statistics by William M. Bolstad (2004) 



5.     Lee,  P.M.  Bayesian  Statistics,  an  Introduction,  Oxford  University 

       Press, New York (1991). 



6.     O.Hagan   A.   Kendall’s   Advanced   Theory   of   Statistics   (Vol.2B), 

       Bayesian Inference, Cambridge, The University Press (1994). 



STAT- 423:        Statistical Quality Control 



Concept     of  quality   control  and    Quality   assurance,    Total   Quality 

Management (TQM) Statistical Methods in Quality Improvement, Statistical 

Process Control (SPC), Statistical Quality Control (SQC), Shewhart control 

charts:   philosophy,   construction,    advantages.    CUSUM       and   moving 

average control charts: Average Run Length (ARL); Fast Initial Response 

(FIR). ARL and FIR for control charts 



Process   capability   analysis:   Process   improvements   using   design   of 

experiments. 



Acceptance  sampling  for  attributes  and  variables,  Acceptance  sampling 

plans: Single, double, and multiple sampling plans with their O.C. curves, 

Military Standard 501 Sampling Plans. Introduction to ISO- 9000 and ISO- 

14000 series 



Pre-Requisite:             STAT-301 



Recommended Books: 



1.     Banks,  J.  (1989).  “Principles  of  Quality  Control”.  John  Wiley,  New 

       York. 



2.     Feigenbaum, A.V. (1986). “Total Quality Control”. McGraw-Hill, New 

       York. 



3.     Juran,   J.M.   and   Guyana,   F.K.   (1988).   “Juan’s   Quality   Control 

       Handbook”. McGraw Hill New York. 



4.     Miltag  H.  J.  and  Rinne  H.  (1993).  “Statistical  Methods  of  Quality 

       Assurance” , Chapman & Hall, London. 



5.     Montgomery,      D.C.   (2013).   “Introduction   to  Statistical  Quality 

       Control”. McGraw Hill, New York. 



6.     Nelson, W. (1990). “Accelerated Testing” . John Wiley, New York. 



7.     Ryan,  T.P.  (1989).  “Statistical  Methods  for  Quality  Improvement”. 

       John Wiley, New York. 



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                           Recommendations 



The following  recommendations were made by the committee to enhance 

the teaching and learning of Statistics: 



1.     Departments  of  Statistics  in  the  universities  should  make  efforts  to 

       interact with national and international statistical organizations such 

       as  PBS,  industry  and  other  users  of  statistics  in  the  public  and 

       private sector. 



2.     Internship  should  be  funded  by  the  HEC  and/or  other  funding 

       agencies, and offered to the students. 



3.     All   universities’   departments   should   develop   and   maintain   an 

       internship  /  career  services  department  to  facilitate  the  internship 

       students of Statistics. 



4.     Most of the courses may be taught using statistical packages. 



5.     Since there is a shortage of highly qualified statisticians in Pakistan. 

       Therefore,  allocating  extra  quota  for  statistics  students  to  pursue 

       higher education is needed. 



6.     The committee strongly recommends the creation of “Department of 

       Biostatistics”  for  teaching  and  research  guidance  at  all  medical 

       colleges/universities     and    the   posts    of   biostatisticians    in  all 

       hospitals/other institutions. 



7.     Practicum conducted during the course work should be in the form of 

       case studies. The data published by different organizations may be 

       used in such case studies. 



8.     A  course  on  Statistics  may  be  added  in  curriculum  of  FSc  (Pre- 

       Medical   &   Pre-Eng.)   to   prepare   students   for   their   professional 

       education. 



9.     The  department  of  Statistics  in  each  university  may  establish  a 

       statistics  consultancy  center  to  attract  potential  researchers.  HEC 

       should  provide  technical  and  financial  support  to  these  research 

       cells. 



10.    Refresher courses for the faculty should be regularly arranged by the 

       HEC. 



11.    HEC  should  support  universities  for  the  development  of  computer 

       labs,   departmental   libraries,   students   and   staff   participation   in 

       seminars, workshops, and conferences. 



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 12.   The department websites  should be updated on a regular basis so 

       that research interests of the faculty may become public. 



 13.   PGD (Post Graduate Diploma) / Short courses should be offered by 

       the universities/department of Statistics to the non-statisticians. 



 14.   Professional  ethics  should  be  an  integral  part  of  the  training  of 

       students at both the undergraduate and graduate level. 



 15.   Since 4 year BS Programme is equivalent to old M.Sc. Programme 

       in Statistics, therefore, the relevant recruitment rules for the post of 

       BPS-17  may  be  amended  by  the  concerned  departments  (FPSC, 

       Establishment  Division)  and  B.S.  (Four  year  Programme)  may  be 

       added in the eligibility criteria for the posts. 



 16.   The department of Statistics in each university should make concrete 

       efforts   for   establishing university-industry   linkages   for   MS   level 

       research. 



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                            Annexure “A” 



COMPULSORY COURSES IN ENGLISH FOR BS 

(4 YEAR) IN BASIC & SOCIAL SCIENCES 



English I        (Functional English) 



Objectives:   Enhance language skills and develop critical thinking. 



Course     Contents 



           Basics of Grammar 

About Author Aamir Rana

Aamir Rana is a Web Designer and an addicted Blogger. He is admin of official website of Govt Emerson College Multan and its social media accounts. Purpose of creating this blog is to facilitate students by providing them all updates regarding education. You can catch him on social media links given below.

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