This page calculates either sample size or power for a one sample binomial problem. Users choose between a one-sided and two-sided test and specify the null and alternative hypothesized proportions. The calculator also gives the critical value.
This page calculates either sample size or power for a one sample binomial problem. Users choose between a one-sided and two-sided test and specify the null and alternative hypothesized proportions. The calculator also gives the critical value.
This site contains links to and descriptions of over 600 applets that can be used for demonstrations or analysis of topics commonly covered in introductory statistics courses.
The BUGS (Bayesian inference Using Gibbs Sampling) project is concerned with flexible software for the Bayesian analysis of complex statistical models using Markov chain Monte Carlo (MCMC) methods. This site is primarily concerned with the stand-alone WinBUGS 1.4.1 package, which has a graphical user interface and on-line monitoring and convergence diagnostics. This program can be downloaded for free from the site.
This Java applet demonstrates confidence intervals for the mean. It allows the user to alter sample size, samples taken, intervals, and the option of standard error. The applet displays sample values, such as average, standard deviation, and percent covered.
Submitting your spotlight presentation from USCOTS 2005 to CAUSEweb is an easy process, and you are in a prime position to submit your work! What better way to have your work showcased than in a peer-reviewed repository of contributions to statistics education? This Webinar from January 2006 provided an opportunity to talk about how to prepare your USCOTS spotlight for submission to CAUSEweb and to discuss the benefits of submission.
This page calculates either estimates of sample size or power for differences in proportions. The program allows for unequal sample size allocation between the two groups.
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.