week 5: correlation

Question 1

Types of Variables in Research

Answer 1

Dependent Variable (DV)
Independent Variable (IV)
Mediating and Moderating Variables

Question 2

Dependent Variable (DV)

Answer 2

The values of the DV are dependent on other variables

we measure

Question 3

Independent Variable (IV)

Answer 3

one we change

Question 4

Major Types of Research Design

Answer 4

Experimental

Naturalistic/observational research

Question 4

Major Types of Research Design

Answer 4

Experimental

Naturalistic/observational research

Question 5

Experimental research

Answer 5

direct and controlled manipulation of IV
can control other extraneous variables
make stronger case for cause and effect relationship

Question 6

Naturalistic or observational research

Answer 6

less control but more naturalistic
can determine strength of relationship
cannot determine cause and effect

Question 7

x and y variables

Answer 7

Variable X:
independent variable (IV)
predictor variable
Variable Y:
dependent variable (DV)
criterion variable

Question 8

summarising methods for variables

Answer 8

Graphically: scatterplot
Numerically: correlation

Question 9

Patterns of linear relationship

Answer 9

Positive relationship: as scores on IV go up, so do scores on DV
Negative relationship: as scores on IV go up, scores on DV go down
No relationship: scores on IV have no relationship with those on DV

Question 10

relationships on linear

Answer 10

positive relationship: when line falls away to the left
negative relationship: when line falls away to the right
zero correlation: when a low score on variable is associated with low, medium and high scores on the other, shape of scatterplot is roughly circular, r=0

Question 11

Correlation

Answer 11

the extent to which two variables are related (change with each other)

Question 12

how do we measure Correlation?

Answer 12

correlation coefficient (r)

Question 13

Calculating the correlation coefficient r

Answer 13

1. decide which variable to call X (IV) and which to call Y (DV)
2. for each score, calculate its corresponding Z score (Zx, Zy)
3. multiply the Zx by the Zy to get the crossproduct
4. add all the crossproducts (SIGMA:ZXZY) and divide by the number of pairs of scores

Question 14

correlation relationship

Answer 14

positive correlation = mostly positive crossproducts
negative correlation = mostly negative crossproducts
no correlation = equal number of + and - crossproducts

Question 15

Interpreting correlation

Answer 15

causality

Question 15

Interpreting correlation

Answer 15

causality

Question 16

causality

Answer 16

correlation cannot tell us exactly which variable is causing which

Question 17

3 possibilities of causality

Answer 17

X causing Y
Y causing X
a 3rd factor could be causing both X and Y

Question 18

what does correlation tell us

Answer 18

correlation tells us direction and strength of a linear relationship

Question 19

why do we square correlation coefficient

Answer 19

if we square the correlation coefficient (r2) we get a more meaningful value

Question 20

squared correlation coefficient (r2)

Answer 20

r2 tells us the proportion of variability in DV that is related to the IV
if r = .8, r2 = .64; proportion of variance accounted for = 64%
(variance NOT explained = 100%-64%=36%)

Question 21

when is correlation large?

Answer 21

healthy correlations in psychology are generally not enormous (.4 - .5).

Question 22

Limitations to r

Answer 22

range restriction