Swinburne University of Technology - Melbourne Australia
Future Students - Courses
Duration
Contact Hours
Campus
Prerequisite
Corequisite
1 Semester /teaching period
3 Hours per Week
Online
Nil
HMS770 Statistical Practice 1. Note: Students studying HMS771 must have either previously studied HMS770 or be currently studying it.
Credit Points: 12.5 Credit Points
An online unit of study in the Graduate Certificate of Science (Applied Statistics), Graduate Diploma of Science (Applied Statistics)) and Master of Science (Applied Statistics)).
To extend the ideas developed in Statistical Practice 1 to include more advanced analyses.To broaden the range of applications students are familiar with, so that they will be able to carry out independent statistical investigations.To develop an awareness of the assumptions and limitations involved in the generalisation of results of such investigations.
Online teaching Voluntary weekend workshops at the Hawthorn Campus
Online quizzes 10%Assignments 30% Examination 60%
This unit of study will contribute to helping students achieve some of the attributes expected of Swinburne graduates. The graduate attributes which relate to this unit of study help to produce students who: Are capable in their chosen professional areas: Students will attain mathematical and statistical knowledge and skills that will support their professional work. This will include abilities in critical enquiry, an awareness of the relationship between statistical theory and practice and an appreciation of the limitations of statistical models. Are adaptable and manage change: Problem-solving and research skills are parts of statistical abilities and enable students to investigate problems and issues of their own devising as well as those covered in this unit.
This unit of study will contribute to helping students achieve some of the attributes expected of Swinburne graduates. The graduate attributes which relate to this unit of study help to produce students who:
Extension of statistical inference to testing means for more than two groups, using analysis of variance for single factor and two factor designs with interaction. An introduction to power analysis. Inference for simple regression, testing regression assumptions using residual analysis and data transformations. Non-parametric methods for testing medians in single, related and independent groups (eg Binomial, sign, Wilcoxon, Friedman, Kruskal-Wallis). Analysis and interpretation of crosstabulations, including measures of association. Special emphasis is placed on reporting the results. ANOVA Review of variance and t-tests. Introduction to the analysis of variance - the single factor, independent groups design. Using SPSS to produce an analysis of variance. Reporting an analysis of variance Analytical comparisons in the single factor independent groups design The Completely Randomised Factorial Design and report writing Analysis of Variance for the Single Factor Within Subjects, and report writing The Mixed Factorial Design, Regression and Nonparametric Methods Correlation, Regression, Inference for Regression Investigation the Assumptions of Regression, Data Transformations Association between two ordinal variables Association between two categorical variables, review of the chi-square test Measuring the strength of the association in tables Non-parametric methods for single and related groups. Non-parametric methods for independent groups. Choosing the correct statistical Test
Extension of statistical inference to testing means for more than two groups, using analysis of variance for single factor and two factor designs with interaction. An introduction to power analysis. Inference for simple regression, testing regression assumptions using residual analysis and data transformations. Non-parametric methods for testing medians in single, related and independent groups (eg Binomial, sign, Wilcoxon, Friedman, Kruskal-Wallis). Analysis and interpretation of crosstabulations, including measures of association. Special emphasis is placed on reporting the results.
ANOVA
Review of variance and t-tests. Introduction to the analysis of variance - the single factor, independent groups design.
Using SPSS to produce an analysis of variance. Reporting an analysis of variance
Analytical comparisons in the single factor independent groups design
The Completely Randomised Factorial Design and report writing
Analysis of Variance for the Single Factor Within Subjects, and report writing
The Mixed Factorial Design,
Regression and Nonparametric Methods
Correlation, Regression, Inference for Regression
Investigation the Assumptions of Regression, Data Transformations
Association between two ordinal variables
Association between two categorical variables, review of the chi-square test
Measuring the strength of the association in tables
Non-parametric methods for single and related groups.
Non-parametric methods for independent groups. Choosing the correct statistical Test
Guarnieri, I. HMS772 Statistical Practice 2: Regression and Non Parametric Methods, Swinburne University Press Francis, G. Analysis of Variance and Interaction. Frenchs Forest: Pearson Australia Available from the Swinburne BookshopIBM SPSS Statistics Software ( At the very minimum the Graduate Pak)
Cohen, J., Statistical Power Analysis for the Behavioral Sciences. NJ: Hillsdale, Erlbaum,. Field, A.P., Discovering Statistics Using SPSS for Windows: Advanced Techniques for the Beginner. London: Sage. Gravetter, F.J. & Wallnau, L.B, Statistics for the Behavioral Sciences, Belmont, CA.: Wadsworth.
