TEC2306

Analytical methods 2

C Varsavsky

4 points · 26 lectures and 13 practice classes · Second semester · Caulfield

Objectives At the completion of this subject, students will be able to apply techniques of data analysis including both traditional and exploratory data analysis (EDA) approaches, to apply inferential techniques to confidence intervals, hypothesis testing, regression and correlation, and to apply linear programming techniques.

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. Linear programming: graphical techniques, simplex methods. Use of statistical software.

Assessment Examination (2 hours): 70% · Assignments and tests: 30%

Recommended texts

Moore D S The basic practice of statistics Freeman, 1995

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