310533 (v.1) Statistical Data Analysis 501

Area:	Department of Mathematics and Statistics
Credits:	12.5
Contact Hours:	3.0
The tuition pattern below provides details of the types of classes and their duration. This is to be used as a guide only. For more precise information please check your unit outline.
Lecture:	1 x 2 Hours Weekly
Tutorial:	1 x 1 Hours Weekly
Syllabus:	Introduction to SPSS. Important terminology. Types of data. Univariate statistics: Graphical displays. Numerical summaries. Transformations. Graphical evaluation of bivariate data. Normal distribution. Tests of normality. Random Sampling. Principles of design of experiments. Sampling distribution of the mean. Introduction to inference. Confidence interval and hypothesis test for using z. Checking assumptions, Type I & II errors. Comparison of classical and p-value approach to hypothesis testing. Hypothesis testing on SPSS. Inference for using the Paired t-test. Difference between means: independent case. Tests on SPSS. ANOVA using SPSS. Examples from different areas. Transforming data or using non-parametric techniques where necessary.
To ensure that the most up-to-date information about unit references, texts and outcomes appears, they will be provided in your unit outline prior to commencement.
Field of Education:	010103 Statistics
SOLT (Online) Definitions*:	Essential *Extent to which this unit or thesis utilises online information
Result Type:	Grade/Mark

Availability

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