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MC265 Introductory Statistics


MC265 Introductory Statistics

Credits: 10 Convenor: Mr. B. English Semester: 1 (weeks 1 to 6)


Prerequisites: essential: MC160
Assessment: Coursework: 20% One and a half hour examination: 80%

Lectures: 18 Classes: 5
Tutorials: none Private Study: 52
Labs: none Seminars: none
Project: none Other: none
Total: 75


Explanation of Pre-requisites

The module MC160 provides the basic probabilistic ideas for an introductory course in statistical methods.

Course Description

Statistics and statistical statements are almost unavoidable in many areas modern science. This course introduces some of the central ideas of modern statistical reasoning, and presents a number of the more basic procedures of elementary applied statistics.

Aims

To introduce the main concepts of statistical inference; point and interval estimation, and hypothesis testing. The likelihood function and maximum likelihood estimate, key concepts in much modern statistical analysis, are also introduced.

Objectives

On completion of this module, students should:

Transferable Skills

Syllabus

Basic graphical methods and descriptive statistics.

Different approaches to inference. Point estimation; mean squared errors, variance and bias. Estimates, estimators and sampling distributions. Standard unbiased estimators of a population mean and variance. Likelihood and the maximum likelihood estimator.

Hypothesis testing and confidence intervals. Inferences for the normal, binomial and Poisson distributions. Comparing two populations. Small sample results for normal populations; the t-test. Paired and unpaired samples, the F and $\chi^2$ distributions.

Simple examples of the $\chi^2$ goodness-of-fit test.

Reading list

Recommended:

M. H. DeGroot, Probability and Statistics, 2nd edition, Addison-Wesley, 1986.

J. E. Freund and R. E. Walpole, Mathematical Statistics, 3rd edition, Prentice-Hall.

W. Mendenhall, R. L. Scheaffer and D. D. Wackerly, Mathematical Statistics with Applications, 4th edition, Duxbury Press, 1990.

Details of Assessment

The final assessment of this module will consist of 20% coursework and 80% from a one and a half hour examination during the January exam period. The 20% coursework contribution will be determined by students' solutions to coursework problems. The examination paper will contain 4 questions with full marks on the paper obtainable from 3 complete answers.


next up previous
Next: Year 3 Up: Year 2 Previous: MC264 Linear Statistical Models
S. J. Ambler
11/20/1999