Statistics
ST312: Applied Statistics II (5 ECTS)
Methods and applications in applied statistical inference. This module discusses factors for consideration in experiment design and demonstrates methods in the analysis of data emerging from desiged experiments. Topics covered include confounding, blocking, a completely randomized design and a randomized block design, two-way ANOVA. The module also demonstrates regression modelling for a qualitative response, i.e. methods in logistic regression and generalized linear models, and various techniques in analysis of a multivariate response, including topics from, principal components analysis, cluster analysis, time series analysis etc. This module is built on ST311.
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:
- discuss topics in experiment design and carry out analysis for data collected from a completely randomized design, a randomized block design, and two-factor studies with interaction effects, interpret the results with reference to the data application;
- formulate a logistic regression model and generalized linear model for a qualitative response, calculate and interpret estimated coefficients and make statistical inferences on the fitted model by carrying out statistical tests using parameter estimates, obtain fitted values and predictions at new data points, together with associated prediction and confidence intervals;
- apply various techniques in analysis of a multivariate response, including topics from, principal components analysis, cluster analysis, time series analysis.
- carry out analysis and testing procedures discussed with the use of software, Minitab;
- compile a statistical report, i.e. prepare a typed document which introduces the statistical research question being explored, describes the data collection method applicable to the research, describes relevant features of the sample data obtained, and outlines conclusions from inferential statistical analysis carried out using the sample data, incorporating output and plots from statistical software.
Indicative Content
This module continues with demonstration in applied statistics with applications in experiment design, modelling techniques for a qualitative response and methods in the analysis of a multivariate response. The analysis is demonstrated with the use of statistical software, MINITAB. Topics discussed in experiment design include confounding of variables, randomization and blocking, and the analysis of data produced from experiments with a completely randomized design, a randomized block design and two-factor studies with interaction effects. Modelling techniques for a qualitative response include logistic regression and generalized linear models. Methods in the analysis of a multivariate response include topics from, principal components analysis, cluster analysis, time series analysis.
Module Resources
Ann R. Cannon et al. STAT2 : building models for a world of data.
Applied Linear Regression Models by Kutner, Nachtsheim & Neter; McGraw Hill
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