Statistical methods
P Grossman (Caulfield) and R Farmer (Peninsula)
4 points * 26 lecture hours * Second semester * Caulfield/Peninsula
Objectives To apply techniques of data analysis including both traditional and exploratory data analysis (EDA) approaches and to apply inferential techniques to confidence intervals, hypothesis testing, regression and correlation.
Synopsis Data analysis. Graphical methods of data presentation. Measures of central tendency and variation. Introduction to exploratory data analysis methods; stem and leaf plots, letter value displays, box plots. Comparison of different samples using traditional and EDA methods. Probability and probability distributions. Simple probability applications. Binomial distribution. Normal distribution. Central limit theorem. Estimation and inference. Confidence interval for the mean for large and small samples. Hypothesis tests on the mean for large and small samples. Hypothesis test on the binomial parameter p. Sign test. Regression and correlation. Scatter plots; sample regression equation. Confidence interval for the mean value of the dependent variable. Sample correlation coefficient and interpretation.
Assessment Examination (3 hours): 70% * Assignments: 30%
Prescribed texts
Adlem R G W TEC2222 (Statistical methods) Monash U, 1996
Recommended texts
Walpole R E and Myers R A Probability and statistics for engineers and scientists 3rd edn, Macmillan, 1985
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