Area: | Department of Mathematics and Statistics |
Credits: | 25.0 |
Contact Hours: | 6.0 |
Lecture: | 2 x 2 Hours Weekly |
Tutorial: | 2 x 1 Hours Weekly |
Anti Requisite(s): | 7149 (v.7) Principles of Statistics 101 or any previous version
307591 (v.1) Data Evaluation and Experimental Design 103 or any previous version
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Prerequisite(s): | 307590 (v.1) Data Evaluation and Experimental Design 101 or any previous version
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Syllabus: | Designed for students with TEE Applicable Mathematics and covers the topics of probability theory, analysis of categorical data, regression analysis, and non parametric methods. |
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Unit Outcomes: | On completion of this unit students will have - Demonstrated an understanding of basic probability concepts including Bayes' theorem. Performed modeling using various distributions and probability calculations associated with bivariate distributions. Gained an understanding of and used functions of random variables. Identified the role of statistics in their own and related discipline areas. Used graphical and numerical displays to perform initial diagnosis of data. Gained an understanding of the basic principles of design of experiment and design simple comparative experiments. Demonstrated practical expertise associated with the use of a statistical package in performing basic statistical procedures. Demonstrated basic knowledge of assessing the appropriateness of statistical models. Demonstrated the use of test and confidence interval for means and applied them in their own discipline areas. Applied decision making process on the means for more than two populations based on the analysis of variance (ANOVA) techniques. Analysed categorical data and drawn appropriate conclusions relating to proportions. Analysed cross classified frequency data. Used Pearson's Chi square test. Completed categorical data analysis using logistic regression. |
Texts and references listed below are for your information only and current as of September 30, 2003. Some units taught offshore are modified at selected locations. Please check with the unit coordinator for up-to-date information and approved offshore variations to unit information before finalising study and textbook purchases. |
Unit References: | Coakes S.J., and Steed, L.G.(2001). Analysis without Anguish. Version 10.0 for Windows. Brisbane, John Wiley and Sons. Moore D. S. and McCabe R.G.P. (1998). Introduction to the Practice of Statistics, 3rd ed. New York, Freeman. Smith P.J. 1993. Into Statistics. South Melbourne, Nelson. Ross S.M. (1999). Introduction to Probability and Statistics for Engineers and Scientists, 2nd ed. San Diego, Wiley. Montgomery D.C., and Runger G. C. (1999). Applied Statistics and Probability for Engineers. New York, John Wiley and Sons. |
Unit Texts: | Walpole, Myers and Myers. (2002). Probability and Statistics for Engineers and Scientists, 7th ed. New Jersey, Prentice Hall. |
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Unit Assessment Breakdown: | Final exam 60%, Module tests (2) or assignments (2) 20%, Regular on-line testing 20%. This is by grade/mark assessment. |
Field of Education: | 10100 Mathematical Sciences (Narrow Grouping) | HECS Band (if applicable): | 2 |
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Extent to which this unit or thesis utilises online information: | Essential | Result Type: | Grade/Mark |
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Availability
| Year | Location | Period | Internal | Area External | Central External | | 2004 | Bentley Campus | Semester 2 | Y | | |
Area
External | refers to external course/units run by the School or Department, offered online or through Web CT, or offered by research. |
Central
External | refers to external course/units run through the Curtin Bentley-based Distance Education Area |
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