STATISTICS COURSE OUTLINE

University of Nigeria, Nsukka.

Note: Depending on the lecturer teaching the course and nature of the text used for a particular course, there may be completely, little or no change to the following course outline:

Statistics students should check their department or meet their academic/staff adviser to confirm some of their courses which have being merged and have their information changed to be sure.

STA        111         Probability I | 2 Units

Elementary set theory. Techniques of counting. Sample space and events. Basic notions of probability. Definition, axioms and laws. Simple conditional probability and independence.

STA        112         Probability II | 2 Units

One dimensional random variables (Discrete and continuous): Definition moments and their distribution: Applications to Bernoulli, Binomial, Geometric, Poisson, Normal, Exponential and hyper-geometric distributions.

STA        131         Inference | 2 Units

Statistical Data: Source, collection and Analysis. Measure of Central Tendency and dispersion, Skewness, moments and Kurtosis. Index numbers and Demographic Measures.

STA        132         Inference II | 2 Units

Elementary Time Series Analysis. Sampling and Statistical inference. Standard error and sampling distributions of the mean and proportion. Tests of significance for one Population means and proportions. Simple linear Regression and Correlation.

STA        172         Statistical Computing I | 2 Units

Generation of data using table of random numbers. Presentation and analysis of data. Computations involving: Times series, index numbers, simple linear regression and correlation. Test of significance (one sample only).

STA        201         Statistics for Social Sciences I | 2 Units

Sources, collection, analysis and presentations of data. Index numbers, elementary analysis of time series; simple linear regression and correlation. Elementary non-parametric tests.

STA        202         Statistics for Social Sciences II | 2 Units

Introductory probability, Binomial, Normal and Poisson distributions. Interval estimation and test of significance. Association of Attributes.

STA        203         Statistics for Agricultural and Biological Sciences I | 2 Units

Initial steps in the planning of biological experiments. Characteristics of well planned experiment. Design of simple biological experiments. Frequency distributions, Elementary probability. Binomial, Poisson and Normal Distributions, Interval Estimation.

STA        204         Statistics for Agricultural and Biological Sciences II | 2 Units

Test of significance. Regression and correlation Analysis. Analysis of variance: One way, two ways (no interaction). Analysis of covariance. Simple analysis of direct assays.

STA        205         Statistics for Physical Sciences and Engineering I | 2 Units

Frequency Distributions. Elements of Probability. Discrete Probability Distributions: Binomial, Poisson, Geometric and Hyper-geometric; Continuous Probability distributions: Normal, students t, chi-square(X² ) and F.

STA        206         Statistics for Physical Sciences and Engineering II | 2 Units

Estimation: Point and interval. Test of significance. Regression and Correlation. Analysis of Variance: One way and two ways (no interaction).

STA        211         Probability III | 2 Units

Combinatorial analysis. Probability models for the study of random phenomena in finite sample spaces up to and including Baye’s Theorem. Probability distribution of Discrete and continuous two dimensional random variables. Expectation and Univariate moment generating functions. Truncated Distributions.

STA        212         Probability IV | 2 Units

Tehebychev’s inequality. Normal approximation to Binomial distribution. Bivariate, Marginal and conditional distributions and their moments. Convolution of two distributions.

STA        231         Inference III | 3 Units

Estimation: By method of moments and maximum likelihood (Binomial, Poisson, Normal distribution). Properties: Unbiasedness, Consistency and efficiency, interval Estimation for means, proportion amd their differences. [STA 232 outlines]: Test of simple Hypothesis: for one and two samples from Binomial and Normal distributions. The performance of a test. Contingency tables model, measures of association and test of independence.

STA        272         Statistical Computing II | 2 Units

Computations involving: Points and Interval Estimation, Test of simple hypothesis, Goodness of fit tests.

STA        311         Probability V | 2 Units

Probability Generating function. Bivariate Normal distribution: Conditional and marginal densities. Bivariate moment generating functions. Inversion formula.

STA        321         Distribution Theory | 2 Units

Bivaraite Normal Distribution, the gamma, Chi-square, 2 types of Beta, F and t distribution of functions of random variables – sums, products and quotients. Probability integral transformation. Order statistics and their functions.

STA        322         Regression Analysis I | 2 Units

Simple linear and Multiple linear Regression models, polynomial regression. Test of goodness of fit. Inference on the regression parameters. Use of dummy variables and examination of residuals. Reparametrization of Non-Linear models.

STA        324         Biometrics I | 2 Units

Direct Assays: types, nature and examples; precision of estimates, fiellers theorem, dilution assays. And design of assays. Indirect Assays: the doseresponse regression, condition of similarity and monotony. Linearizing transformations and non-linear regression.

STA        325         Biometrics II | 2 Units

Parallel line assays: unsymmetrical designs, difference in preparations, potency estimation and fiducial limits and validity test. Approximate and exact analysis for missing entries. Symmetry design for parallel line assays. Efficiency, reliability and Sensitivity.