## General information

This web site started as a response to students' remarks and concerns regarding the fast paced introductory statistics classes held at Iowa State University. Students’ comments consistently mentioned wanting faster answers to their questions, more examples, and more instruction in the statistical package JMP. Due to the limited classroom time during a semester we decided to develop mini video tutorials as our response to address the students’ concerns. This web site provides a compilation of these video tutorials along with a short description of the content of each video.

Although the videos included here are thorough, we want to stress that these videos are not meant to replace classroom instruction but are instead intended to supplement existing lectures. Each video will provide instruction regarding at least one of four main areas including: graphically displaying data, numerically summarizing data, general statistical techniques, and interpreting statistical results. Videos emphasizing graphical displays and statistical summaries utilize the statistical package JMP and include data sets if the user would like to follow along. Videos focusing on statistical techniques and interpreting results will include worksheets and/or handout. For best results, we recommend printing out any accompanying worksheets and/or handouts before viewing each video.

## Topic Descriptions

Graphical Displays -- how to use JMP to create graphs and charts for univariate data: bar charts, pie charts, pareto charts, histograms, boxplots, and stem-and-leaf plots.

Using Statistical Tables -- using the standard normal distribution table and using the t distribution table

Normal Distribution -- finding areas under the standard normal distribution, 68-95-99.7 rule, finding areas under any normal distribution, backwards normal calculations, creating normal quantile plots in JMP

Sampling Distributions -- taking random samples in JMP, properties of the sampling distribution of , determining if x̄ is normal (Central Limit Theorem), and probability/area calculations of the sampling distribution of

Confidence Intervals for μ -- confidence interval for μ when σ is known, finding critical t-values, confidence interval for μ when σ is unknown, margin of error and confidence interval width, and sample size calculations related to confidence intervals for μ.

Hypothesis Tests for μ -- hypothesis tests for μ when σ is known, hypothesis tests for μ when σ is unknown, finding p-values, interpreting p-values, hypothesis test and confidence interval equivalence, and hypothesis testing for μ in JMP.

Simple Linear Regression -- making a scatterplot in JMP, correlation, fitting simple linear regression model in JMP, parameter calculations, parameter interpretations, R2 interpretation, confidence intervals for parameters, hypothesis tests for parameters, confidence intervals for parameters in JMP, checking assumptions, creating normal quantile plot of residuals in JMP, creating residual plot in JMP, getting predicted y-values in JMP, confidence and prediction intervals for predicted y-values, and getting confidence and prediction intervals for predicted y-values using JMP

Multiple Linear Regression -- fitting a multiple linear regression model in JMP, parameter interpretations, R2 interpretation, interpreting RMSE, conducting a global F test, confidence intervals for parameters, hypothesis tests for parameters, confidence intervals for parameters in JMP, checking assumptions, creating normal quantile plot of residuals in JMP, creating residual plot in JMP, getting predicted y-values in JMP, confidence and prediction intervals for predicted y-values, getting confidence and prediction intervals for predicted y-values using JMP, multicollinearity, creating scatterplot matrix in JMP, getting VIF values in JMP, and variable/model selection in JMP

ISU JMP Scripts -- JMP script for sampling distribution of , JMP script for hypothesis tests, and JMP script for confidence intervals for μ.