In this demonstration a scatterplot is displayed and you draw in a regression line by hand. You can then compare your line to the best least squares fit. You can also try to guess the value of Pearson's correlation coefficient.
This applet demonstrates that even a "small" effect can be important under some circumstances. Applicants from two groups apply for a job. The user manipulates the mean and the cut-off score in order to see the effects the small changes has on the number of people hired in each group. The effects on the proportion of hired applicants from each group are displayed.(Requires a browser that supports Java).
This free online video program "shows how to improve the accuracy of a survey by using stratified random sampling and how to avoid sampling errors such as bias. While surveys are becoming increasingly important tools in shaping public policy, a 1936 Gallup poll provides a striking illustration of the perils of undercoverage."
In this free online video program, "students will learn the distinction between deterministic phenomena and random sampling. This program introduces the concepts of sample space, events, and outcomes, and demonstrates how to use them to create a probability model. A discussion of statistician Persi Diaconis's work with probability theory covers many of the central ideas about randomness and probability."
The Data Library contains lists of ongoing data-sharing projects, downloadable data sets in Excel spreadsheet format, and other sources of data found on the web.
This activity guides students through the process of checking the validity of data, performing summary analysis, constructing box plots, and determining whether significant differences exist. The data comes from a study of mineral levels in older adults and is available in Minitab, Excel, SAS, and text formats.
This material is a detailed exercise for students in introductory statistics. Students are asked to collect a random sample of data from a real estate website; conduct descriptive statistics (including confidence intervals); and write a report summarizing their dataset. The primary learning goals are to teach students 1) how to obtain a random sample; 2) how to interpret confidence intervals; 3) how to simulate and interpret a sampling distribution; and 4) how to communicate descriptive statistics.
This site contains data sets to help teach a Chance course and help students understand issues that may not be found in a standard statistics text. Topics covered include: mean, median, random walks, regression, correlation, and more.
