Level: II
Semester: 2
Number of Credits: 3
Prerequisites: MATH 2274


Course Description

The course is a survey of the major ideas of inference, experimental design and statistical methods. The course may be viewed as consisting of three closely connected parts. In the first section, students are introduced to the basics of the statistical packages Minitab and R and their use in descriptive statistics. Emphasis is placed on the use of real data and both summary statistical measures and graphical descriptive devices for continuous and discrete data are discussed. In the second section, we discuss the frequentist theory of inference, including point estimation, confidence intervals and hypothesis testing. Section three is devoted to various statistical methods. The major ones are regression models and the use of ANOVA in designed experiments. Several of the important basic designs are discussed. We also discuss methods for the analysis of discrete data, such as in contingency tables, and non-parametric procedures.

A knowledge of Probability Theory I is assumed. This is needed since we derive the distributions of most statistics that are used and also discuss systematic mathematical methods for finding point estimators and constructing tests.



Coursework                                                           50%
Final Examination - one 2-hour written paper   50%
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