STA447 Advanced Business Statistics (8)

CSU Discipline Area: Mathematics and Statistics (MASTA)

Duration: One session

Abstract:

This subject examines the use of statistical tools available for analysis. Statistical techniques are examined within typical applications. Topics include inferences about differences of means and proportions; standard deviation; comparison of variances; chi squared tests of goodness-of-fit and independence; analysis of variance; multiple linear regression; factor analysis; binary regression; further business forecasting methods and non-parametric statistics. Extensive use is made of a statistical computer package. Students should be able to use the skills developed in this subject to support their work in practical problems.

+ Subject Availability Modes and Locations

Session 1
Distance	Bathurst

Continuing students should consult the SAL for current offering details: STA447

Where differences exist between the Handbook and the SAL, the SAL should be taken as containing the correct subject offering details.

Enrolment restrictions:

Not available to students who have completed STA217 or STA201 or QBM217

Objectives:

Upon successful completion of this subject, students should:

. be able to demonstrate an understanding of the theoretical foundations underlying different statistical techniques;
. be able to demonstrate appreciation of the assumptions and consequent limitations of each technique;
. be able to identify and apply appropriate statistical methods in a variety of applications;
. be able to employ recognised industry standard software to carry out the necessary data storage, manipulation and analysis;
. be able to use and interpret the results of statistical analyses in practical problems.

Syllabus:

The subject will cover the following topics:

. Review of elementary concepts of statistical inference concerning a mean and a proportion. . Inference on a pair of means or a pair of proportions. . The Chi-squared distribution and inference on a single standard deviation. Tests of goodness-of-fit and of independence of two qualitative variables. . The F distribution and inference on a pair of variances. . One-way analysis of variance, and multiple comparisons of treatment means, and underlying assumptions. . Simple linear regression, interpretation and inference on the regression as a whole, the regression coefficients. The underlying assumptions and residuals analysis. . Multiple linear regression, interpretation and inference on the regression as a whole, the regression coefficients. Underlying assumptions and residuals analysis, polynomial regression, transformations. Multicollinearity, and factor analysis. . Binary regression, interpretation and inference on the regression as a whole. Underlying assumptions and residual analysis. . Nonparametric tests, including Wilcoxon rank sum and signed ranks, runs and Spearman's rank correlation, and Kruskal-Wallis test.

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