4469 (v.3) Applied Statistics 503

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Area:	Department of Mathematics and Statistics
Credits:	25.0
Contact Hours:	3.0
Lecture:	2 x 1 Hours Weekly
Practical:	1 x 1 Hours Weekly
Other Requisite(s):	Admission: upon prior completion of undergraduate unit(s) in statistics
Syllabus:	Review exploratory data analysis - t-tests and non-parametric equivalents, power analysis. Experimental design and analysis of variance - review of one-way analysis of variance model, model diagnostics, multiple comparison techniques, principles of experimental designs, ANOVA for some standard experimental designs like randomized block design, Latin square design, split plot and nested design, factorial method of experimentation and analysis, experiment with repeated measures and analysis of covariance. Examples of applications using SPSS. Multiple linear regression - review of simple linear regression. The multiple linear regression model, parameter estimation and inferences about the regression parameters, F-testing overall model fit, variable selection and the stepwise algorithm for variable selection, model diagnostics, prediction. Examples of applications using SPSS. Multivariate methods - introduction, principal component analysis, clustering, discriminant analysis and MANOVA. Examples of applications using SPSS. Introduction to contingency tables and models for discrete.
Unit Outcomes:	On successful completion of this unit students will have gained the ability to explain the differences between designed experiments and observational studies, perform exploratory data analysis, conduct hypothesis testing and estimation using both parametric and non-parametric techniques for simple comparative experiments involving one or more groups, design simple comparative experiments to draw objective conclusions, explain construction of randomized block designs, latin square designs, split plot designs and nested designs and analyze data resulting from such experiments, analyze outputs from simple repeated measure designs, apply technique of analysis of covariance, model data arising from real life situations using general linear modelling, perform multivariate analysis for dimensionality reduction, clustering, discriminating and comparing data across groups (MANOVA) and analyze contingency tables and perform tests for proportions.
Text and references listed above are for your information only and current as of September 30, 2003. Please check with the unit coordinator for up-to-date information.
Unit References:	Montgomery, D. C., 2001, 'Design and Analysis of Experiments', Fifth Edition, John Wiley and Sons, Mead, R. and Curnow, R. M., 1983, 'Statistical Methods in Agricultural and Experimental Biology'. Chapman and Hall. Chatterjee, S. and Price, B., 1977, 'Regression Analysis by Examples', Second Edition, Wiley-Interscience. Snedecor, G. and Cochran, W., 1980, 'Statistical Methods', Seventh Edition, Iowa State University Press. Steel, R. G., Torrie, J. H. and Dickey, D. A., 1997, 'Principles and Procedures ofStatistics - A Biometric Approach', Third Edition, WBC MGraw-Hill. Milton, J. S. , 1999, 'Statistical Methods in the Biological and Health Sciences', Third Edition, WBC McGraw-Hill. Johnson, R. A. and Wichern D. W., 2002, 'Applied Multivariate Statistical Analysis', Fifth Edition, Prentice Hall. Digby, P. G. N. and Kemptom, R. A., 1987, 'Multivariate Analysis of Ecological Communities', Chapman Hall. Coakes, S. J. and Lyndall, G. S., 2002, 'SPSS. Analysis Without Anguish', Version 10 for Windows, John Wiley & Sons.
Unit Texts:	Ott, R. L. and Longnecker, M., 2001, 'An Introduction to Statistical Methods and Data Analysis', Fifth Edition, Duxbury Press. Gupta, R., 2003, 'Applied Statistics 01, 501, 503' Lecture Notes, Curtin Publication.
Unit Assessment Breakdown:	Open Book Quizzes 5%. Mid Term Test 10%. Project Report 15%. Final Examination 70%.
Year Location Period Internal Area External Central External 2004 Bentley Campus Semester 1 Y