Check out new mobile apps for Explore Data and Regression
Check out new mobile apps for Explore Data and Regression
Explore statistical concepts in an interactive way. Use the apps to construct graphs, obtain summary statistics, find probabilities, get confidence intervals or fit linear regression models. Take screenshots or download graphs of your data.
Construct 2 x 2 contingency tables, obtain conditional proportions and get a bar graph. Find the difference or ratio of proportions to describe the strength of the association. Built the sampling distribution of the difference or ratio via resampling.
Construct interactive scatterplots, hover over points, move them around (or remove them) and overlay a smooth trend line. Find the correlation coefficient r and see if it is robust to outliers. Built the sampling distribution of r via resampling.
Under Construction. In the meantime, use the Multivariate Relationships app, which has some capablities to fit a multiple linear regression model with two explanatory variables.
Under Construction. Fit and visualize a simple exponential regression model to data such as the number of COVID-19 infections in New York City in March 2020 (Example 16, Chapter 13).
Under Construction. Fit a logistic regression model with a single quantitative predictor. Obtain parameter estimates, a graph of the fitted probabilities and construct confidence intervals.
Experience how the sampling distribution of the sample proportion builds up one sample at a time. Use sliders to explore the shape of the sampling distribution as the sample size n increases, or as the population proportion p changes. Overlay a normal distribution to explore the Central Limit Theorem.
Experience how the sampling distribution of the sample mean builds up one sample at a time. Use a variety of real or theoretical continuous population distributions (or create your own) to draw samples from. Move sliders to explore when the Central Limit Theorem kicks in.
Experience how the sampling distribution of the sample mean builds up one sample at a time. Use a variety of real or theoretical discrete population distributions (or create your own) to draw samples from. Move sliders to explore when the Central Limit Theorem kicks in.
Confidence intervals or hypotheses tests about the difference of two population proportions. Obtain the margin of error or the z-test statistic and visualize the interval or the P-value on a graph.
For two independent or dependent samples.
Find the bootstrap or permutation distribution for the difference or ratio of two proportions, or for the odds-ratio. Use these to obtain percentile confidence intervals or permutation P-values for testing whether there is no association.
Under Construction
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