# Software Resources for Data Desk

Below is a list of resource pages for using Data Desk to do statistics. On each page a set of data are explored with the software. Some commentary is given on interpretation but the main focus is on getting the software to do the work. What the numbers mean should come from your prior statistical training or the statistics.com course you are currently taking. Each page listed below has a title you can click on to read the page. Beneath the title is a list of topics covered on that page.

## Getting Started

• Starting Data Desk
• Entering data
• Simple summary statistics
• Histograms
• Boxplots
• Logarithmic transformations

## Summarizing Quantitative Data

• Simple summary statistics comparing two groups
• Boxplots comparing two groups
• Transformations
• Interpreting outliers

• Mode
• Tables
• Bar charts
• Pie charts

## Summarizing One or Two Categorical Variables

• One- and Two-Way Tables

## Interpreting Two-Way Tables

• Probability and two-way tables
• Fixing data errors

## Inference for One Proportion

• Confidence interval
• Hypothesis test

## Chi-Squared Tests

• One-way (Goodness of Fit)
• Two-way (Contingency Tables)
• Comparing two proportions

## Inference for a Single Mean

• Confidence interval
• Hypothesis test

## Data Manipulation

• From M/F or Yes/No to 0-1
• Stacking and unstacking variables

## Inference for Two Group Comparisons

• Confidence interval for two means
• Hypothesis test for two means
• Confidence interval for paired differences
• Hypothesis test for paired differences
• Ad hoc methods for proportions

## Simple Linear Regression

• Opening data files
• Simple plots for each variable
• Scatterplots
• Correlation and covariance
• Running a regression
• Scatterplot with regression line
• Inference for regression coefficients
• Regression through the origin
• Making predictions (limited support)

(Data Desk does not compute the Durbin-Watson statistic.)

## Regression with Two Independent Variables

• Reading data from a text file
• Correlations
• Regression with one or two independent variables
• Brief discussion of multicollinearity and autocorrelation
• Basic residual plots

## Multiple Regression with Quantitative Independent Variables

The link takes you to a page describing the example data from which you can then link to pages for different software packages.

• Scatterplots
• Running a multiple regression
• Regression diagnostics
• Detecting and dealing with outliers
• Predictions (limited support)
• Residual plots

## Transformations

• Boxplot of one variable
• Scatterplot of two variables
• Doing common transformations with Data Desk
• Assessing the impact of a transformation

## Multiple Regression with Qualitative Independent Variables I

The link takes you to a page describing the example data from which you can then link to pages for different software packages.

• Scatterplots with two subgroups shown
• Creating indicator (0-1) variables for two groups
• Running a multiple regression with a 0-1 variable
• Interpreting a multiple regression with a 0-1 variable
• Creating interaction terms
• Running a multiple regression with an interaction term
• Interpreting a multiple regression with an interaction term
• Predictions (limited support)

## Multiple Regression with Qualitative Independent Variables II

• Scatterplots with three or more subgroups shown
• Creating indicator (0-1) variables for three or more groups
• Running a multiple regression with multiple 0-1 variables
• Interpreting a multiple regression with multiple 0-1 variables
• Creating interaction terms
• Running a multiple regression with two or more interaction terms
• Interpreting a multiple regression with two or more interaction terms
• Testing a subset of the independent variables

## One-way Analysis of Variance

• Opening data files
• Boxplots comparing multiple groups
• ANOVA

## Two-way Analysis of Variance

• Finding subgroup means