Material Detail

This app focuses on conducting a t-test and checking the normality condition. Both the one-sample and two-sample t-tests are implemented in this app. Recall that for the t-test to be valid either sample size(s) need to be large enough or the population distribution(s) needs to be a Normal distribution. To begin the app, data configuration is required. Users have the choice to either use sample data or upload their own data when first launching the app. Customization is needed in respect to the uploaded data. After selecting their option, users can proceed to visualizing the data. A histogram is presented for one sample while comparative boxplots are presented for two samples. In addition, summary statistics are also available for display.

The hypothesis test tab displays the null and alternative hypotheses. The settings available for users to adjust are the hypothesized value, the direction for the alternative hypothesis, and the significance level. For users who are not familiar with the concept of the hypothesis test, they can click on a link that shows information in a popover. Additional information on the one-sample and two-sample t-tests is also available. When users have run the t-test, the output includes items such as the shaded t-distribution, t-statistic, and the p-value. The point estimate(s) and confidence interval can also be outputted by users’ request. In the normality condition tab, the Shapiro-Wilk normality test is performed and a Q-Q plot is displayed. In all relevant outputs throughout the app, sample interpretations from popovers are included for users to understand the results of the hypothesis test.

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