Generate a graphic and numerical display of the properties of the Normal Distribution. For a unit normal distribution, with M=0 and SD=α1, enter 0 and 1 at the prompt. For a distribution with M=100 and SD=α15, enter 100 and 15. And so forth
Generate a graphic and numerical display of the properties of the Normal Distribution. For a unit normal distribution, with M=0 and SD=α1, enter 0 and 1 at the prompt. For a distribution with M=100 and SD=α15, enter 100 and 15. And so forth
In this applet, we simulate a series of hypothesis of tests for the value of the parameter p in a Bernoulli random variable. Each column of red and green marks represents a sample of 30 observations. "Successes'' are coded by green marks and "failures'' by red marks.
This chapter of the HyperStat Online Textbook discusses in detail sampling distributions of various statistics (mean, median, proportions, correlation, etc.), differences between such statistics, the Central Limit Theorem, and standard error, giving formulas, examples, and exercises.
Log-linear analysis is a version of chi-square analysis in which the relevant values are calculated by way of weighted natural logarithms. This page will calculate several values of G^2.
In the first simulation, random samples of size n are drawn from the population one sample at a time. With df=3, the critical value of chi-square for significance at or beyond the 0.05 level is 7.815; hence, any calculated value of chi-square equal to or greater than 7.815 is recorded as "significant," while any value smaller than that is noted as "non-significant." The second simulation does the same thing, except that it draws random samples 100 at a time. The Power of the Chi-Square "Goodness of Fit" Test pertains to the questionable common practice of accepting the null hypothesis upon failing to find a significant result in a one- dimensional chi-square test.
As the page opens, you will be prompted to enter the sizes of your several samples. If you are starting out with raw (unranked) data, the necessary rank- ordering will be performed automatically.
As the page opens, you will be prompted to enter the sizes of your several samples. If you are starting out with raw (unranked) data, the necessary rank- ordering will be performed automatically.