This section of an online textbook discusses calculating the exact probability using observed sets of frequencies, constructing frequency tables, and computing p-values. Exercises and answers are provided.
This site is part of an online textbook and discusses non-parametric tests. It explains the calculations, assumptions, and uses of the Wilcoxon ranked sum test. How to treat unpaired and paired samples is covered. Related exercises and answers are included.
This section of an online textbook discusses the correlation coefficient and illustrated it visually through graphs. It explains calculations as well as how scatter plots can describe data. It covers significance tests for relationships, the Spearman rank correlation and the regression equation. Exercises and answers are included.
This article provides a data collection and analysis activity for illustrating simple linear regression and outlier analysis. The activity was designed to involve students in the process of data collection and to motivate studying the relationship between two quantitative variables. Students collect data on occurrences of letters in English text. These data are used to study the relationships between how often a letter occurs in English text, and: (1) the letter's Morse Code units and (2) the relative frequency of Scrabbleä‹¢ game tiles for the letter. Worksheets and answers to the activities are provided.
This dataset contains the time of birth, sex, and birth weight for 44 babies born in one 24-hour period at a hospital in Brisbane, Australia. The data can be used for studying some common distributions like the normal, binomial, geometric, Poisson, and exponential.
The dataset presented in this article comes from a South African study of growth of children. This data is a useful example of Simpson's paradox. Key Words: Categorical data; Comparing proportions.
This article presents a dataset containing physical measurements for 507 physically active individuals. These data can be used to demonstrate simple descriptive statistics, least squares and multiple regression, or discriminant and classification analysis. The data are in .dat format.
This article describes a dataset containing information for 25 brands of domestic cigarettes. The dataset can be used to illustrate multiple regression, outliers, and collinearity.
The dataset presented in this article contains information on the prices and weights of diamond stones; it can be used to illustrate simple linear regression and encourage students to think critically about the appropriateness of a model. The data is in .dat format. Key Words: Extrapolation; Interpretation of intercept; Model-building; Transformations.
