Duration: 2 Days

Overview: This course teaches how to analyze data with a single continuous response variable using analysis of variance and regression methods. You learn how to perform elementary exploratory data analysis (EDA) and discover natural patterns in data. Important statistical concepts such as confidence intervals are also introduced.

Learn how to

Use JMP software to:

  • compare two means using a t-test
  • generate and interpret an analysis of variance to compare more than two means
  • analyze relationships between continuous variables using simple and multiple linear regression models
  • perform an analysis of covariance to incorporate continuous and categorical predictors
  • evaluate assumptions in statistical hypothesis testing.

Pre-requisites: Before attending the course, you should complete the JMP Software: A Case Study Approach to Data Exploration course or have equivalent experience.

This course uses JMP software.

Who: Analysts and researchers with some statistical knowledge


Introduction to Statistics

  • statistical concepts
  • descriptive statistics and some of their graphs
  • inferential statistics
  • hypothesis tests

Comparing Means

  • one-sample t-test
  • paired t-test (self-study)
  • two-sample t-test

Analysis of Variance

  • one-way ANOVA with two groups
  • one-way ANOVA with more than two groups
  • fitting an N-way ANOVA model
  • contrasts in N-way ANOVA (self-study)
  • power and sample size

Simple Linear Regression

  • exploratory data analysis
  • simple linear regression
  • polynomial regression

Multiple Regression

  • fitting a multiple regression model
  • fitting a multiple regression model with interactions
  • generating and comparing candidate models

Regression Diagnostics

  • evaluating assumptions
  • influential observations
  • collinearity

ANCOVA (Self-Study)

  • fitting an analysis of covariance (ANCOVA) model