Postgraduate School
Postgraduate Diploma in Statistics
| Name | Status and Qualifications | Research Interests |
| G. M. Oyeyemi | Professor & Head of Department B.Sc., M.Sc., Ph.D. (Ilorin) | Multivariate Analysis |
| B. L. Adeleke | Professor B.Sc. (Ilorin); Dip. Agric Stat. (Washington); M.Sc., Ph.D. (Ilorin) | Design and Analysis of Experiment |
| A.. A. Adewara | Professor B.Sc., M.Sc., Ph.D., PGDE (Ilorin) | Sample Survey Methods and Applications |
| A. O. Adejumo | Professor B.Sc., M.Sc. (Ilorin); Ph.D. (Munich). | Modelling, Biostatistics, Time Series & Categorical Data Analysis |
| W. B. Yahya | Professor N.C.E.(Ila-Orangun); B.Sc., M.Sc. (Ilorin); PGDFM, MBA (Ado- Ekiti); Ph.D. (Munich) | Microarray Analysis, Modelling, Data Mining, Categorical Data Analysis, Bayesian Inference & Biostatistics |
| A. A. Abiodun | Reader B.Sc., M.Sc., Ph.D. (Ilorin) | Survival Analysis & Statistical Modelling |
| A. O. Abidoye | Reader B.Sc.(Ilorin); M.Sc. (Ibadan); Ph.D. (Ilorin) | Biostatistics and Hypothesis Testing |
| O. Job | Senior Lecturer NCE (Ilorin); B.Sc., M.Sc., Ph.D. (Ilorin) | Econometrics |
| M. K. Garba | Senior Lecturer B.Sc., M.Sc., Ph.D.(Ilorin) | Econometrics, Time Series and Statistical Modeling |
| I. Oloyede | Senior Lecturer N.C.E.(Ila-Orangun); PGDS (UNAAB, Abeokuta); B.Sc.(OAU, Ile-Ife); M.Sc.(Ago-Iwoye); Ph.D. (Ilorin) | Bayesian Inference, Econometrics and Statistical Learning |
| N. A. Ikoba | Senior Lecturer B.Sc.; M.Sc. (OAU. Ile-Ife ); Ph.D. (Ilorin) | Stochastic Processes and Applications, Distribution Theory, Demography |
| A. W. Banjoko | Senior Lecturer B.Sc , M.Sc., Ph.D.(Ilorin) | Microarray Data Analysis, Biostatistics and Statistical Quality Control |
| R. B. Afolayan | Lecturer I B.Sc , M.Sc., Ph.D.(Ilorin) | Design and Analysis of Experiments, Regression Analysis, Biometry |
| Olakiitan I. | Lecturer I | Survival Analysis |
| Adeniyi | B.Sc , M.Sc., Ph.D.(Ilorin) | |
| Mariam O. Adeleke | Lecturer I B.Sc., M.Sc. (Ilorin); M.Sc. (London); PhD. (London) | Medical Statistics |
| O. R Olaniran | Lecturer I B.Sc., M.Sc. (Ilorin); Ph.D. (UTM) | Data Mining, Bayesian Inference and Biostatistics |
| L. B. Amusa | Lecturer I B. Sc., M.Sc. (Ilorin); Ph.D. (KwaZulu-Natal) | Data Mining, Statistical Modelling, Biostatistics |
| Jumoke Popoola | Lecturer I B.Sc., M.Sc., Ph.D. (Ilorin) | Operations Research, Stochastic Processes and Mathematical Statistics |
| Ifeyinwa V. Omekam | Lecturer II B.Sc. (UNN, Nssuka); M.Sc. , Ph.D. (Ilorin) | Distribution Theory |
Introduction
The programme is to offer expert teaching and supervision in various aspects of theory and applications of statistics as follows: Analysis of Variance and its Applications, Categorical Data Analysis, Design and Analysis of Experiments, Econometrics, Modeling, Multivariate Analysis, Biostatistics, Repeated Measurements and Analysis, Sample Survey and Sampling techniques, Statistical Quality Control and its Application, Survival Analysis, Stochastic Processes, Time Series Analysis, and Statistical Computing. A holder of the Postgraduate Diploma in Statistics will be equipped with the skills needed to begin a career as a professional statistician.
C. Philosophy
The philosophy of the programme is anchored on the unbiased and systematic observations, accurate documentation and interpretation of facts and phenomena with view to generate a body of knowledge. Lecturers from home and abroad were on ground and made significant contributions.
D. Aim and Objectives
The aim of the programme is to allow candidates who cannot apply for M.Sc. in Statistics directly to acquire additional qualification that can pave the way for them into M.Sc. Statistics.
The objectives of the programme are to enable:
E. Admission Requirements
Candidates for admission to the programme shall be selected from amongst those who hold:
In addition, all candidates must have 5 credit passes at GCE/O Level including English Language and Mathematics (at least any 2 from Physics, Chemistry, Geography, Further Maths, Economics).
F. Duration of the Programme
The duration of PGD in Statistics shall be a minimum of nine (9) Calendar months and a maximum of twelve (12) months.
G. Detailed Course Description
STA701 Probability and Distribution Theory 3 Credits
Sample Space, Events. Definitions and basic results of probabilities. Conditional Probability and independence, Bayes Theorem. The Binomial and Poisson Distribution and the Normal Approximation. Random variables, Expectation (Mean, Variance and higher moments), Chebychev‘s Inequality, Law of large numbers and the Central Limit Theorems. Generating functions, Distribution function of random variables and of the sum, difference, product and Quotient of two random variables. Student‘s t, F and distributions. 45h (T); C
STA702 Design and Analysis of Experiments 3 Credits
Basic concepts and principles of experimentation, randomization, Replication and Error control. Complete randomized, randomized block and Latin Square designs. Orthogonality and transformations. Analysis of standard designs. Missing plot techniques. Factorial experiments with factors at two levels. Confounding and Factorial replication. Applications of designs to areas of human activity–namely Agriculture, Industry etc. 45h (T); C
STA703 Statistical Methods 3 Credits
Sampling Distributions of statistics. Test of significance concerning means, Proportions and Variance using z, t, and F statistic Contingency tables and
test of goodness of fit. Linear regression and correlation, Partial, Multiple regression and correlation. Tests concerning correlation and regression coefficients. ANOVA for one way and two – way experiments. 45h (T); C
STA704 Statistical Inference 3 Credits
Point estimation by Methods of Moments, Least Square, Maximum, Likelihood and some properties of point estimation. Unbiasedness, Sufficiency, Completeness etc. Fisher‘s information. Crammer – Rao inequality. Interval Estimation. Tests of hypotheses. Neyman- Pearson theorem, Sequential Analysis. Non- parametric tests. 45h (T); C
STA705 Multivariate Analysis 3 Credits
Multivariate distribution and associated Marginal and Conditional distributions. Estimation of mean vector and variance matrix. Test of hypotheses, hoteling‘s T And Mahalannobis D Discrimination and Classification. Principal Components and Factor Analyses. 45h (T); E
STA706 Operation Research 3 Credits
Stochastic, and non – stochastic models in Operation Research. Linear, non linear, integer and dynamic programming. Application to transportation, storage and shortest route and other related problems. 45h (T); E
STA707 Statistical Quality Control 3 Credits
Basic concepts. Specification and Inspection of quality characteristics. Control charts for mean, ranges and standard deviation. Control charts for numbers of defective effects per unit and number of defectives. Acceptance sampling procedure in single, double and multiple sampling plans, Lot-by-lot sampling inspection by attributes and by variables. Continuous Sampling plans. 45h(T); C
STA708 Design And Analysis of Sample Survey 3 Credits
Basic concepts. The role of the sampling method. Principal steps of a sample Survey. Estimation of means, totals, ratio and proportions in simple random and Stratified sampling. Ratio and regression estimation. Systematic sampling. Sampling with probabilities proportional to size. Cluster sampling and Multivariate sampling. Errors in surveys. 45h (T); C
STA709 Introduction to Economic and Social Statistics 3 Credits
General Survey of Nigeria economic and social statistics; Main sources, Uses and Limitations. Economic Index numbers. Laspeyres. Pasches‘s, and Fisher‘s Formula. Customer price index and other applications of index number. Health Education, Housing and Crime Statistics. Statistical Organization in Nigeria. 45h (T); E
STA710 Statistical Computing 3 Credits
Fundamental components of Computers. Programming in BASIC and FORTRAN Languages, Computation of mean, variance, correlation and other moments. Sorting and ranking of data, Use of some statistical packages, like SPSS and SAS for statistical analysis. 45h (T); C
STA711 Econometric Method 3 Credits
Basic concepts of econometrics. Two variable linear models. Econometric Problems related to single equation. Simultaneous equation methods, Identification and estimation. Tests of specification and misspecification, predictive and non – predictive and various hypotheses, Multicolinearity, Generalised least square, linear restrictions, dummy variables, Dynamic models Application of econometric models in production, consumption and investment functions. 45h (T); E
STA712 Demographic Methods 3 Credits
Sources of population data: Census, Vital registration, and surveys (demographic and morbidity). Census organization and problems. Measures of fertility, Mortality and nuptality. Construction of life tables. Population growth and projection. 45h (T); E
STA799 Practical Project 5 Credits
The project shall involve collection, analysis and interpretation of primary or Secondary data on a topic in statistics approved by the Department. 225h (P); C
Graduation Requirements
For the award of PGD certificate in Statistics, a student must pass a minimum of 33 Credits comprising 27 Credits of Compulsory courses and 6 Credits of Elective courses.
I. Summary
Compulsory Courses:
STA701 (3), 702 (3), 703 (3), 704 (3), 707 (3), 708 (3), 710 (3), 799 (5) 27 Credits
Elective Courses (Minimum of two Courses) from Elective Courses listed below.
Minimum of 6 Credits
Elective Courses
STA705 (3), 706 (3), 709 (3), 711 (3), 712 (3)
Minimum Total Graduation Requirements 33 Credits
CLASSIFICATION OF PGDS PROGRAMME AWARD.
The final determination of an award will be based on the Cumulative Grade Point Average (CGPA) earned at the end of the programme
Distinction – 4.50 – 5.00
Credit – 3.50 – 4.49
Pass – 3.00 –- 3.49
Fail – Below 3.00
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