|
 Academic Year:
| 2015/6 |
| Owning Department/School:
| Department of Mathematical Sciences |
| Credits:
| 6 |
| Level:
| Intermediate (FHEQ level 5) |
| Period: |
Semester 1 |
| Assessment Summary:
| CW 25%, EX 75% |
| Assessment Detail: |
|
| Supplementary Assessment: |
MA20226 Mandatory extra work (where allowed by programme regulations) |
| Requisites: | Before taking this module you must take MA10211 AND take MA10212 |
| Description:
| Aims: Introduce classical estimation and hypothesis-testing principles. Learning Outcomes: After taking this unit, students should be able to: * Perform standard estimation procedures and tests on normal data. * Carry out goodness-of-fit tests and analyse contingency tables. * Use R to calculate estimates, carry out hypothesis tests and compute confidence intervals. Skills: Numeracy T/F A Problem Solving T/F A Computing Skills T/F A Written and Spoken Communication F (in tutorials). Content: Point estimation: Maximum-likelihood estimation, including computational aspects; further properties of estimators, including mean square error, efficiency and consistency; robust methods of estimation such as the median and trimmed mean. Confidence intervals. Hypothesis testing: Size and power of tests; Neyman-Pearson lemma. One-sided and two-sided tests. Distributions related to the normal: t, chi-square and F distributions. Interference for normal data: Tests and confidence intervals for normal means and variances, one-sample problems, paired and unpaired two-sample problems. Contingency tables and goodness-of-fit tests. Examples of all the above, including case studies in R. |
| Programme availability: |
MA20226 is Compulsory on the following programmes:Department of Mathematical Sciences
MA20226 is Optional on the following programmes:Department of Mathematical Sciences
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