SSregression = SStotal * rsquared

SSerror = SStotal * (1- rsquared)

SStotal = SSy

df(regression) = k – 1

df(error) = N – k

df(total) = N-1

F = mean squares regression divided by means squares error

 

Formula for Central Tendency

MEAN.

You probably already know this formula. A mean is the average of scores. We like to use it becuase we don’t have to arrange the scores in any particular order before calculating it. We just add up all the numbers and divide by the number of scores. In statistical vocab we “sum” the numbers and divided the sum by N (the number of scores).

∑X/N

MEDIAN

A median requires that we put the numbers in order (from high to low, or low to high). The median is the score in the middle (if there are an odd number of scores) or the average of the two middle-most scores (if there are an even number of scores). That too much work, so we prefer the mean.

There is no easy formula for median.

MODE

The mode is the most popular score (most common). If you plot a distribution, the mode will be the highest spot on the distribution. It will be the top of the mountain. If your mountain has more than one peak, the distribution will be bimodal (2 high spots) or multimodal (several high spots).

There is no easy formula for mode.