STA3202 Statistical Inference

The focus of this introductory course is estimation and hypothesis testing in which we estimate various unknown parameters of the populations. Illustrations of applications in real life are made such as inferences about the mean, measure of variation, and proportions.

General Course Objectives
By the end of the course, the participants should be in a good position to:

• To Define random sampling, sampling techniques and standard error of the mean
• To compute levels of significance
• To compute levels of significance involving differences between two means
• To conduct tests involving population variances
• To work with inferences involving population proportions 

Expected Learning Outcomes
By the end of the course, the student should be able to:

• Select a random sample and determine all possible random samples of a given size from a given population.
• Demonstrate that the sample mean is a random variable and determine its sampling distribution and distinguish between the standard deviation and the standard error.
• Use appropriate methods to estimate and test hypothesis of the various measures of central tendency and spread and apply the methods to solve practical problems.
• Determine appropriate sample sizes for estimating various parameters and differences between parameters in practical problems.