Regression analysis > Regression in Minitab
Watch the video or read the steps below:
How to find Regression in Minitab
Regression is fitting data to a line (Minitab can also perform other types of regression, like quadratic regression). When you find regression in Minitab, you’ll get a scatter plot of your data along with the line of best fit, plus Minitab will provide you with:
- Standard Error (how much the data points deviate from the mean).
- R squared: a value between 0 and 1 which tells you how well your data points fit the model.
- Adjusted R2 (adjusts R2 to account for data points that do not fit the model).
Regression in Minitab takes just a couple of clicks from the toolbar and is accessed through the Stat menu.
Example question: Find regression in Minitab for the following set of data points that compare calories consumed per day to weight:
Calories consumed daily (Weight in lb): 2800 (140), 2810 (143), 2805 (144), 2705 (145), 3000 (155), 2500 (130), 2400 (121), 2100 (100), 2000 (99), 2350 (120), 2400 (121), 3000 (155).
Step 1: Type your data into two columns in Minitab.
Step 2: Click “Stat,” then click “Regression” and then click “Fitted Line Plot.”
Step 3: Click a variable name for the dependent value in the left-hand window. For this sample question, we want to know if calories consumed affects weight, so calories is the independent variable (Y) and weight is the dependent variable (X). Click “Calories” and then click “Select.”
Step 4: Repeat Step 3 for the dependent X variable, weight.
Step 5: Click “OK.” Minitab will create a regression line graph in a separate window.
Step 4: Read the results. As well as creating a regression graph, Minitab will give you values for S, R-sq and R-sq(adj) in the top right corner of the fitted line plot window.
s = standard error.
R-Sq = Coefficient of Determination
R-Sq(adj) = Adjusted Coefficient of Determination (Adjusted R Squared).
If you prefer an online interactive environment to learn R and statistics, this free R Tutorial by Datacamp is a great way to get started. If you're are somewhat comfortable with R and are interested in going deeper into Statistics, try this Statistics with R track.Comments are now closed for this post. Need help or want to post a correction? Please post a comment on our Facebook page and I'll do my best to help!