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Mathematical Statistics
STM 312 :
Advanced Mathematical Statistics A1
Contents:
Transformation of random variables, Order statistics, Families of random variables,
Sampling distributions, Limiting distributions and stochastic convergence, Point
estimation and properties of estimates, Quadratic
forms, Multivariate normal distribution. (16 Credits)
Pre-requisites: STM221 or STM222
STM 313 :
Introductory Applied Statistics B1
Purpose:
Learners are to acquire advanced knowledge of
statistical techniques applied in deriving optimal
methods of analysing data.
Contents:
Normal Z-score test for one and two independent
populations . Student’s t-test for one and two
independent populations. Mann-Whitney U-test.
Paired samples t-test and Wilcoxon’s Signed rank
test for two dependent populations. One-way fixed
effects ANOVA, Kruskal-Wallis test and Two-way
fixed effects ANOVA for tests concerning more than
two independent populations. Least significant
difference and Honestly significant difference-
Tukey, Scheffe for Multiple comparison procedures.
Chi-square goodness of fit test and Chi-square test for independence for testing the
association between categorical variables. (16 Credits)
Pre-requisites: STM221 or STM222
STM 322 :
Advanced Mathematical Statistics A2
Purpose:
Learners are to acquire an introductory knowledge of statistical software packages
and develop skills in computerised statistical data analysis.
Contents :
Theory and Applications of interval estimation. Statistical hypothesis testing. Simple
and composite hypotheses. Uniformly most powerful tests and likelihood ratio tests.
Analysis of Variance. The general linear model. Chi-squared tests and tests of
independence. Sufficiency. The Rao- Cramer lower bound. (16 Credits)
Pre-requisites: STM312
STM 323 :
Introductory Applied Statistics B2
Purpose:
Learners are to acquire an introductory knowledge of statistical software packages
and develop skills in computerised statistical data analysis.
Contents :
Correlation Analysis: Pearson’s coefficient of simple correlation. Spearman’s
coefficient of simple correlation. Partial correlation. Simple Linear Regression:
Simple linear regression
parameter estimation and interpretation. Tests for
significance of a regression. Relationship with correlation analysis. Response
prediction. Multiple Linear Regression Analysis: Parameter estimation and
interpretation. Variable selection procedures. Pearson’s coefficient of multiple
determination. Adjusted coefficient of determination. Multicollinearity. Handling
Problem Data: Missingness. Outlying values. Violation of statistical assumptions.
Diagnostic and remedial measures. (16 Credits)
Pre-requisites: STM313
Statistics show that of
those who contract the
habit of eating, very
few survive.
Learners are to acquire an
advanced knowledge of the
statistical techniques
applied in the derivation of
optimal methods for
analysing data.
THIRD YEAR COURSES