Regression

Question 1

what does it mean to say that simple linear regression is descriptive and inferential?

Answer 1

it describes form, direction, and strength of a relationship and predicts the value of y when we have values of x

Question 2

what does simple linear regression minimize?

Answer 2

the sum of squares

Question 3

compare simple linear regression with Pearson’s r

Answer 3

-similar techniques, tend to be used in conjunction with each other
- regression has more precise descriptions

Question 4

what differentiates simple linear regression from Pearson’s r?

Answer 4

regression can predict the value of y using the value of x

Question 5

what is multiple regression able to control for?

Answer 5

multiple IVs

Question 6

what are the assumptions of simple linear regression?

Answer 6

1. continuous, (minimally) interval data
2. normal distribution on both IV and DV
3. simple random sampling
4. absence of non-sampling errors
5. linearity
6. homoscedasticity

Question 7

what is homoscedasticity?

Answer 7

all x and y values deviate equally from the slope

Question 8

what is heteroscedasticity?

Answer 8

x and y values deviate inconsistently from the slope

Question 9

what is the constant/intercept?

Answer 9

value of y/DV when x/IV is 0

Question 10

what is a slope?

Answer 10

the steepness of the regression line; for every unit of change in x/IV, the corresponding change in y/DV is…

Question 11

in the regression formula, what does “a” stand for?

Answer 11

the constant/intercept

Question 12

in the regression formula, what does “b” stand for?

Answer 12

the slope

Question 13

what is the predictive aspect of regression?

Answer 13

the slope