MAS5052 Basic Statistics
Note: This is an old module occurrence.
You may wish to visit the module list for information on current teaching.
|Both semesters, 2019/20||20 Credits|
|Lecturer:||Dr Sammy Rashid||Reading List|
|Outcomes||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.
Learning outcomesBy the end of the unit students should have an understanding of: - the basic concepts of statistical inference and of rational decision-making under uncertainty - how these concepts may be applied in a wide range of practical circumstances. - appropriate software to be used in conjunction with these methodologies.
Directed reading from the textbooks listed below; discussion boards; coursework assignments.
No lectures, no tutorials
Formal Examination, Coursework
- 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
|A||Miller, I. and Miller, M.||John E. Freund's Mathematical Statistics with Applications (8th edition)||Blackwells||Amazon|
|A||Moore, D. S., McCabe, G. P., and Craig B. S.||Introduction to the Practice of Statistics (edition 9 or 8)||Blackwells||Amazon|
(A = essential, B = recommended, C = background.)
Most books on reading lists should also be available from the Blackwells shop at Jessop West.