Summary of Regression

The variable with the smallest standard deviation is the easiest to predict. The less dispersion, the easier to predict.

Without knowing anything else about a variable, the best predictor of it is its mean.

The angle of a regression line is called the slope. Slope is calculated by dividing the Sxy by the SSx.

The point where the regression line crosses the criterion axis is called the intercept.

Predicting the future based on past experience is best done with a regression.

Predicting scores between known values is called interpolation.

Predicting scores beyond known values is called extrapolation.

Regression works best when a relationship is strong and linear.

Regression works best when the correlation is strong.

The error around a line of prediction is consistent along the whole line. It doesn’t vary or waver along the line, so there is only 1 standard error of estimate for the entire line.

The error around a line of prediction can be estimated with the standard error of estimate.

Plus or minus one SEE accounts for 68% of the prediction errors.

A regression is based on paired-observations on the same subjects.

Pre- and Post-test performance is best analyzed by using a regression.

 

NOW YOU CHOOSE:
    Day 6: Regression
    Bit More About Regression
    Even More About Regression
    Calculate Regression
    Practice Problems
    More Practice Problems
    Word Problems
        Sim1       Sim2         Sim3
        Sim4       Sim5         Sim6
        Sim7       Sim8         Sim9
    Basic Facts About Regression
    Vocabulary
    Formulas
    Quiz 6
    Summary