sums of squares

Question 1

total sums of squares

Answer 1

squared distance of each data point from the y mean
- how much variance is in the dependent variable

Question 2

residual sums of squares

Answer 2

squared distance of each data point from the predicted value
- how much of the variation in the dependent variable the model did not explain (unexplained variance in the regression model)

Question 3

What do lower residual sums of squares suggest?

Answer 3

the model fits the data well

Question 4

model sums of squares

Answer 4

deviance of the predicted scores from the mean of y
- how much of the variation in the dependent variable the model explained (how well does the regression line fit the data)

Question 5

sums of squares measure…

Answer 5

quantifies the different sources of deviance/variation of data points from the mean (how spread out the numbers are in a given dataset)