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Statistics

Mathematical Statistics 2

This course consists of the two modules STAT201 and STAT203 which must be passed separately.

  STAT201: Theory of Distributions (20 Credits)

 This module consists of 84 single lectures, 28 practicals and 28 tutorials during the first semester.

 Pre-requisites: A previous pass in STAT101 and STAT102 and MATH104

        Content:

Basic probability concepts. Theory of continuous probability distributions. Expected values and MGF. Special continuous probability distributions: Uniform, Gamma, Exponential, Weibull, Pareto, and Normal. Theory of multivariate discrete and continuous distributions, Marginal and conditional distributions. Covariance and correlation. Theory of conditional expectation and conditional variance. Functions of Random variables: distribution function technique, transformation methods, MGF technique. Limiting distributions and stochastic convergence. CLT and applications. Sampling distributions: Chi-square, t, F, Beta distributions.

 

STAT203: Regression Analysis and Advanced Regression Topics (20 credits)

This module consists of 84 single lectures, 28 practicals and 28 tutorials during the second semester.

Pre-requisites: A final mark of at least 40% for STAT201 or a final mark of at least 40% for STAT202.

Content:

Simple linear regression: The theoretical (mathematical) model, assumptions, estimation, coefficient of determination, prediction, regression through the origin. Multiple linear regression: The model, assumptions, estimation, inferences. Polynomial regression, Second and higher order regression. Testing portions of a model. Stepwise regression. Models with qualitative and quantitative predictors. Model building. Regression pitfalls. Residual analysis. Piecewise regression. Inverse prediction. Weighted least squares regression. Qualitative response variables. Logistic regression. Log-Linear Models. Ridge regression. Robust regression. Model validation.

 

Statistics 2

This course consists of the two modules STAT202 and STAT203 which must be passed separately.

STAT202: Probability, Distribution Theory and Estimation (20 Credits)

This module consists of 84 single lectures, 28 practicals and 28 tutorials during the first semester.

Pre-requisites: A previous pass in STAE101 - 102 and either MATA101 – 102 or MATH101 - 104.

Content:

Probability concepts: Experiment, sample space and events. Computing probabilities: Permutations and combinations. Conditional probability. Bayes' Theorem. Functions associated with random variables. Special Discrete Distributions: Uniform, Bernoulli, Binomial, Hypergeometric, Poisson and Negative Binomial. Special Continuous Distributions: Uniform, Exponential, Gamma, Chi-squared, Beta and Normal. Statistical Inference: Estimation and Hypothesis testing.