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QBM217 Advanced Business Statistics (8)

Abstract

This subject extends the set of statistical tools available for the analysis of business situations. Further statistical techniques are examined within typical business 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.

+ Subject Availability Modes and Location

Continuing students should consult the SAL for current offering details prior to contacting their course coordinator: QBM217
Where differences exist between the handbook and the SAL, the SAL should be taken as containing the correct subject offering details.

Subject information

Duration Grading System School:
One sessionHD/FLSchool of Computing and Mathematics

Assumed Knowledge

STA117 or QBM117

Enrolment restrictions

Not available to students who have completed STA217 or STA201 or STA447
Incompatible subject(s)
STA201 STA217 STA447

Learning Outcomes

Upon successful completion of this subject, students should:
* be able to demonstrate an understanding of the theoretical foundations underlying the 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 industrial and business applications;
* be able to employ recognised industry standard software to carry out the necessary data storage, manipulation and analysis.

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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The information contained in the 2015 CSU Handbook was accurate at the date of publication: 01 October 2015. The University reserves the right to vary the information at any time without notice.