## MAS5052 Basic Statistics

 Both semesters, 2017/18 20 Credits Lecturer: Dr Sammy Rashid Reading List Teaching Methods Assessment Full Syllabus

The module is a distance-learning instrument aimed at graduates who wish to undertake a postgraduate Masters course in Statistics but lack the appropriate mathematical and statistical background. It introduces the basic concepts of statistical inference and of rational decision-making under uncertainty, and it demonstrates how they may be applied in a wide range of practical circumstances. Implementation of the methodology with appropriate software forms an integral part of the unit.

There are no prerequisites for this module.
No other modules have this module as a prerequisite.

## Teaching methods

Directed reading from the textbooks listed below; discussion boards; coursework assignments.

No lectures, no tutorials

## Assessment

Formal Examination, Coursework

## Full syllabus

• Data display and summary; using R.
• Data relationships: scatterplots and correlation, cross tabulation and Simpson's paradox
• Simple linear regression
• Using R for bivariate data
• Introduction to data collection; design of experiments; sampling and sample surveys
• Introduction to inference
• Sampling distribution of a proportion
• Sampling distribution of a mean
• Properties of estimators
• Hypothesis testing
• Use and abuse of testing
• Power and sample size
• Inference as a decision
• Standard tests: one-sample t test; paired t test; tests of location for non-normal data; two-sample z and t tests; chi-squared and F-tests; single proportions; comparing proportions; chi-squared test of association, homogeneity and goodness of fit.
• Inference for simple linear regression; inference for correlation and regression via ANOVA
• Multiple regression
• One-way ANOVA and two-way ANOVA
• Maximum likelihood estimation
• Further uses of likelihood