4. simple regression

Question 1

like correlation

Answer 1

anouther inferntional test about relation between variables

Question 2

difference to correlation

Answer 2

regression analysis on one var can predict score on anouther

Question 3

predictor varibale

Answer 3

similar to iv ( to help understand only) -THERE IS NO ACC IV

Question 4

outcome varible

Answer 4

simialr to DV

Question 5

assume

Answer 5

chnages on var (x) changes anouther (y)
therefore as assume constant relation= (linearty) we now that we can predict one var= if one goes up predict other one ect.
(RELATES TO LINEAR)

Question 6

the assumption of constanct relation is summerised by

Answer 6

line of best fit

Question 7

linear relation

Answer 7

positive= high x assosiated high y
negative high x assosiated with low y

Question 8

perfect linear

Answer 8

-1-perfect neg linear rel
1-per pos linear rel

Question 9

whats regression purpose

Answer 9

extention when 2 variables correlated
regression produces predict scores

Question 10

predicted scores (variables)

Answer 10

outcome var= aim to predict (y)
predictor var- use to predict y (x)
( here use linear relation eg pos or neg)

Question 11

outcome and predict var in axit

Answer 11

outcome=y axis
predictor= x axis