These pages from the University of Melbourne explain statistical concepts using various examples from medicine, science, sports, and finance. The intent is not computational skill but conceptual understanding. Some pages also contain data.
This glossary defines and explains statistical terms for introductory students. The glossary can be shown in alphabetical order or in suggested learning order. Click on the topic of interest to see the definition. Use the arrows at the bottom to proceed to the next topic or click the blue dot to return to the contents page.
This tutorial introduces mean, median, mode, variance, and standard deviation using sports statistics from the Internet and class-generated statistics. Students should understand stem-and-leaf plots before using this tutorial. This material is intended for class use. Excel spreadsheets with sample data are also available for download. The relation links to a letter for teachers.
This article introduces Radial Basis Function (RBF) networks. These networks rely heavily on regression analysis techniques. Topics include Nonparametric Regression, Classification and Time Series Prediction, Linear Models, Least Squares, Model Selection Criteria, Ridge Regression, and Forward Selection.
This tutorial introduces various statistics used to analyze and summarize data. The tutorial covers both the arithmetic and geometric means, median, mode, standard deviation, coefficient of variation, skewness, kurtosis, quadrants, and histrogram analysis. The application is flow cytometry, but others may use this tutorial as well.
This collection of tutorials demonstrates various statistical topics with data and provides SPSS and Minitab code. Topics covered: Measures of Central Tendency; Sign Test; Chi-Square; Mann-Whitney Test; Wilcoxon Matched-Pairs Signed-Ranks Test; Kruskal-Wallis One-Way Analysis of Variance; Friedman Two-Way Analysis of Variance; Spearman Rank Correlation; Pearson Product-Moment Correlation; Multiple Regression; t-Test for Independent Samples; t-Test for Matched Pairs; One-Way ANOVA; Two-Way ANOVA.
This tutorial describes various measures of central tendency, their theory and use, and demonstrates them with an example on final exam scores. Data is given as well as SPSS and Minitab code. Key Words: Mean; Median; Mode; Variance; Standard Deviation.
This tutorial explains the theory and use of Student's t-test and demonstrates it with an example on final exam scores. Data is given as well as SPSS and Minitab code.
