A cartoon suitable for a course website that makes use of a boxplot to display an outlier and also uses the term "statistically significant" in its punch line. The cartoon is number 539 (February, 2009) from the webcomic series at xkcd.com created by Randall Munroe. Free to use in the classroom and on course web sites under a creative commons attribution-non-commercial 2.5 license.
Using the Fisher r-to-z transformation, this page will calculate a value of z that can be applied to assess the significance of the difference between two correlation coefficients, r_a and r_b, found in two independent samples. If r_a is greater than r_b, the resulting value of z will have a positive sign; if r_a is smaller than r_b, the sign of z will be negative.
For a table of frequency data cross-classified according to two categorical variables, X and Y, each of which has two levels or subcategories, this page will calculate the Phi coefficient of association; perform a chi-square test of association, if the sample size is not too small; and perform the Fisher exact probability test, if the sample size is not too large. For intermediate values of n, the chi-square and Fisher tests will both be performed.
This page will compute the t-test for either correlated or independent samples. One may copy and paste data in or type the data in individually.
A joke to teach the meaning of type I error by University of Texas at El Paso professor of Mathematical Sciences, Lawrence Mark Lesser (1964-) and Ohio State Unviersity PRofessor of Statistics Dennis K. Pearl (1951-).
This chapter explains the structure/steps of hypothesis testing, the concept of significance, the relationship between confidence intervals and hypothesis testing, and Type I/II errors.
This text explains the differences between t-tests, z-tests, tests with proportions, and tests of correlation.
When does a significant p-value indicate a true effect? This app will help with understanding the Positive Predictive Value (PPV) of a p-value.
This app is based on Ioannidis, J. P. A. (2005). Why most published research findings are false. PLoS Medicine, 2(8), e124. http://doi.org/10.1371/journal.pmed.0020124
A song that can be used in discussing the meaning and interpretation of Type I error in Significance Testing. The lyrics were written by Mary McLellan from Aledo High School in Aledo, Texas as one of several dozen songs created for her AP statistics course. The song may be sung to the tune of “We Will Rock You,” written by Brian May and recorded by Queen in 1977. Also, an accompanying video may be found at
https://www.youtube.com/watch?v=2qfYYWZ92BY