# Perform a Basic Regression Analysis

Perform a Basic Regression Analysis

## Minitab® – Procedure

The "basic regression analysis" command outputs:

• the estimated regression function
• a table of estimated coefficients (Coef), which also includes standard errors of the coefficients (SE Coef), and t-statistics (T) and P-values (P) for testing the parameters differ from 0
• the coefficient of determination r2
• the analysis of variance table
• a table of unusual observations
1. Select Stat >> Regression >> Regression >> Fit Regression Model ...
2. In the box labeled "Response", specify the desired response variable.
3. In the box labeled "Predictors", specify the desired predictor variable.
4. Select OK. The basic regression analysis output will be displayed in the session window.

### Regression Through the Origin

To fit an RTO model click "Model" in the regular regression window and uncheck "Include the constant term in the model".

## Example

Sports Illustrated published results of a study designed to determine how well professional golfers putt. The data set puttgolf.txt contains data on the lengths of putts and the percentage of successful putts made by professional golfers during 15 tournaments. Only putts that were 2 to 20 feet from the hole are included in the data set.

Is there a significant linear relationship between the response y = success and the predictor x = length?

## Minitab Basic Regression Analysis Dialog Box

### Regression Analysis: success versus length

Analysis of Variance
Source DF Adj SS Adj MS F-Value P-Value
Regression 1 9529 9529.29 113.28 0.000
length 1 9529 9529.29 113.28 0.000
Error 17 1430 84.12
Total 18 10959
Model Summary
S R-sq R-sq (adj) R-sq(pred)
9.17166 86.95% 86.18% 82.51%

Regression Equation

success = 83.61 - 4.089 length

Fits and Diagnostics for Unusual Observations
Obs success Fit Resid Std
Resid
R
1 93.30 75.43 17.87 2.17
R Large residual

## Video Review

 [1] Link ↥ Has Tooltip/Popover Toggleable Visibility