The bias of a measurement describes to what degree it is systematically off target from the true value. The reliability of a measurement describes how consistent the measurement is when you repeat it. This app is designed to help with understanding those concepts.
This app allows the user to examine the sampling distribution of the mean for samples from a variety of continuous and discrete populations.
This game is to help you better understand the numerical value of correlations for scatterplots with or without outliers.
This matching game challenges the user to match summary statistics and graphs and real world situations.
In this App, you will observe the effect of outliers on both histograms and boxplots.
This app focuses on tests for proportions in a sports context (basketball free throw shooting). The app illustrates how a change in the population caused by filtering can change the results and also illustrates the difference between p, p̂, and p0.
This app quizzes your knowledge of hypothesis testing concepts using a tic-tac-toe game format.
The app requires students to engage with inference scenarios for a mean (or difference in means) in context. Users will explore the behavior of confidence intervals for a single mean and two sample tests for the difference in means as the level and sample size changes.
The app requires students to engage with inference scenarios for a proportion (or difference in proportions) in context. Users will explore the behavior of confidence intervals for a single proportion and two sample tests for the difference in proportions as the level and sample size changes.
This app is designed to examine the Law of Large Numbers for means and proportions. The Law of Large Numbers tells us that averages or proportions are likely to be more stable when there are more trials while sums or counts are likely to be more variable.