Minitab help
Use the links below to find information about how to implement statistical analysis methods using Minitab.
- A Five-Minute Introduction to Minitab Statistical Software
- Minitab Procedures
- Calculating a t-interval for population mean μ [R]
- Coding a numeric variable into another numeric variable [11]
- Coding a text variable into a numeric variable [9]
- Conducting a LOF Test [6,7]
- Conducting a Ryan-Joiner correlation test [5,7]
- Conducting best subsets regression [13]
- Conducting stepwise regression [13]
- Creating a basic scatter plot [1,5,6,8,11]
- Creating a correlation matrix [8]
- Creating a fitted line plot [1,2,3,4,5,6,7]
- Creating a fitted line plot with confidence bands and prediction bands [2]
- Creating a scatter plot with each data point characterized by a third variable [2,4,9,11]
- Creating a simple matrix of scatter plots [8]
- Creating interaction terms in your worksheet [11]
- Creating residual plots [5,6,7]
- Determining summary statistics for a variable [2]
- Displaying data
- Finding a confidence interval and a prediction interval for the response [2,4]
- Finding a t-based P-value [R]
- Finding a t-critical value [R]
- Finding a t-multiplier [R,8,9]
- Finding an F-critical value [3]
- Finding an F-based P-value
- Generating random normally distributed data [11]
- Obtaining a sample correlation coeffcient [4]
- Performing a basic regression analysis [1,2,3,4,8,9,11]
- Performing a basic regression analysis (and get a prediction interval) [4]
- Performing a multiple regression analysis — with options [8]
- Performing a t-test for a population mean using raw data [R]
- Randomly sampling (x, y) data with replacement from two columns [1]
- Splitting the worksheet based on the value of a variable [4,5]
- Storing residuals (and/or influence measures) [5,7]
- Other procedures created as we need them!