Statistics
ST113: Statistics (5 ECTS)
The module is intended as a first course in statistics for students studying a degree in which mathematics is to be the main subject throughout that degree as it provides a good foundation to higher level probability and statistics modules. ST112 or its equivalent is a prerequisite for this module.
Taught in Semester(s) II. Examined in Semester(s) II.
Workload: 24 hours (24 Lecture hours).
Module Learning Outcomes.
On successful completion of this module the learner should be able to:
- identify sources of variation in observational and experimental data, identify ideas involved in some basic survey and experimental designs, and be aware of sensitivity of analyses to various assumptions
- summarise data numerically and graphically
- demonstrate how probability is used in the construction of interval estimates and in hypothesis testing, including the computation of p-value and power of tests
- identify and perform some one and two-sample statistical inference procedures for parametric models
- perform basic enumerative data analysis concluding good-of-fit and contingency table tests and tests for equality of several population proportions
- calculate and interpret correlation and conduct analysis for simple linear regression models
Indicative Content
General Aims:
The module begins by reviewing the normal distribution and calculations of probabilities involving normally distributed random variables and means of large random samples from virtually any population. The module demonstrates methods of data summarisation and presentation, including numerical measures of location and spread for both ungrouped and grouped data, and graphical methods including histograms, stem-and-leaf and box plots. The module discusses statistical inference, demonstrating the explanation of statistics through practical examples of its applications, concepts of point and interval estimation, concepts in hypothesis testing including Type I and Type II errors and power, confidence intervals and hypothesis tests. These methods are applied in inference for a single population mean, a single population proportion, the difference between two population means, a single population variance and the ratio of two population variances, the analysis of enumerative data, including chi-squared goodness-of-fit and contingency table tests, correlation and linear regression analysis, including least squares estimation of the parameters of the simple linear regression model, inferences about these parameters, and prediction.
Module Resources
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