This page calculates probabilities for a Poisson distribution.
This page calculates probabilities for a Poisson distribution.
This applet simulates drawing samples from a binomial distribution. Users set the population proportion of success (pi), sample size (n), and number of samples. By clicking "Draw Samples," the applet will draw a sample and display the corresponding sample histogram. Each new sample drawn is added to the previous ones unless the user clicks "Reset" between samples. Users can choose to display the number and proportion of successes above or below a certain value (tail probabilities) by entering a value in the "Num Successes" box and clicking "Count." The portion of the distribution that meets the condition is highlighted in red, and the proportion of success is given at the bottom of the page. Clicking the inequality sign changes its direction. Clicking "Theo Values" displays the theoretical distribution in green on top of the empirical. Instructions and an activity for this applet can be found in the textbook "Investigating Statistical Concepts, Applications, and Methods" (ISCAM) in Lesson 3.2.2 on page 205.
Everyday we have specific routines we engage in. Many of these routines are tailored to preventing us from becoming victims of crime. We do things like lock our doors, watch where we walk at night, or avoid walking alone. We take these actions because at some level we are afraid of the possibility of being a victim of crime. Although we may not consciously think about it, these routines may be influenced by a variety of factors. What factors might make some individuals more afraid than others?
This online calculator allows users to enter 16 observations with up to 4 dependent variables and calculates the regression equation, the fitted values, R-Squared, the F-Statistic, mean, variance, first order serial-correlation, second order serial-correlation, the Durbin-Watson statistic, and the mean absolute errors. It also tests normality and gives the i-th residuals.
This calculator computes the chi-square statistic, degrees of freedom (DoF), and p-value for the Chi-square test for equality of distributions. Users input a table of values with row and column labels without total scores. The null hypothesis is that the all the samples have the same distribution.
This test checks whether an observed distribution differs from an expected distribution. It computes the chi-square statistic, degrees of freedom (DoF), and p-value. Users input a table with row and column labels, observed frequencies on the first row, and expected frequencies on the second row. The null hypothesis is that the observed values have the expected frequency distribution.
This page provides a table of F distribution probabilities for alpha = 0.10, 0.05, 0.025, and 0.01.
This page provides a z-table with alpha levels from .00 to .09.
This page provides a t-table with degrees of freedom 1-30, 60, 120, and infinity and seven levels of alpha from .1 to .0005.
BrightStat is a free online application for statistical analyses. Besides many non-parametric tests, BrightStat offers multiple linear regression, logistic regression, ANOVA and repeated measurements ANOVA as well as Kaplan Meier Survival analysis. BrightStat has an easy to use GUI and supports the creation of mostly used scientifc graphs such as line-, bar-, scatter- and box-plots as well as histograms.