Chapter 9

Question 1

frequency

Answer 1

1 variable

Question 2

association

Answer 2

correlation causality

Question 3

multiple regression

Answer 3

(only continuous), adds second variable
more than one predictor (continuous)
- one outcome (continuous)

Question 4

R

Answer 4

effect of all to the predictor (IV) variables on the dependent variables
-COMBINED effect of all predictor variables on the outcome

Question 5

r

Answer 5

looking at the IV by itself

Question 6

B (greek letter)

Answer 6

effect of one predictor variable on the outcome variable w/o the influence of any other predictor variable
ex- looks at effect of extraversion on texting without any influence on anxiety, talked away shared variance, shared variance of the independent variable

Question 7

B (greek letter)

Answer 7

effect of one predictor variable on the outcome variable w/o the influence of any other predictor variable
ex- looks at effect of extraversion on texting without any influence on anxiety, talked away shared variance, shared variance of the independent variable

Question 8

r2

Answer 8

effect size of r (how big of an effect does the IV have on the DV)
care about both B (greek), significance & p, & multiple R - Squared

Question 9

criteria for causality

Answer 9

covariance
temporal precedence
internal validity

Question 10

covariance

Answer 10

as one variable changes the other variable changes
-causation does not equal correlation but causal requires covariance
ex- as my relationship satisfaction changes, my happiness changes
ex- when the participants had the bracelet on they did better on the balance test than when they didn’t have the bracelet on

Question 11

temporal precedence

Answer 11

one thing comes before the other
IV before the DV
ex- if i think hitting you in the head with cause brain damage then you have to hit me in the head before the brain damage

Question 12

internal validity

Answer 12

IV is actually causing the change in the DV
circle to circle
does the energy frequency really cause better balance?

Question 13

when do you fail to reject?

Answer 13

when p > .05

Question 14

when do you reject the null?

Answer 14

when p < .05

Question 15

what are the steps to looking at if milk & cereal effect your income? mediation relationship

Answer 15

1. run a Pearson r
2. then you run a multiple regression
3. look at beta weights & one the arrows shouldn’t be associated

Question 16

mediation

Answer 16

one variable causes another variable which causes another

Question 17

moderated

Answer 17

blonde doesn’t cause your gender, it effects it