Correlation

Question 1

Correlation

Answer 1

A specific measure of how two variables are related to each other linearly

Question 2

Correlation use 1

Answer 2

Describe pattern of change in values of two factors

Question 3

correlation use 2

Answer 3

determine whether the pattern observed in a sample is also present in the population of the sample

Question 4

Correlation coefficient (R)

Answer 4

Measures strength and direction of the linear relationship

Question 5

Correlation values

Answer 5

between -1.0 and 1.0, the sign indicating only direction or slope

Question 6

R formula

Answer 6

r=SSxy/sqrt(SSx)(SSy)

Question 7

Step 1 in finding correlation

Answer 7

obtain mean of x and mean of y

Question 8

step 2 in finding correlation

Answer 8

obtain deviation of x and deviation of y using means and each x (sum should equal 0)

Question 9

step 3 in finding correlation

Answer 9

multiply the deviation scores (x-Mx)(y-My)

Question 10

Step 4 in finding correlation

Answer 10

Square each individual variation score, both x and y separately

Question 11

Step 5 in finding correlation

Answer 11

SSxy=the sum of the multiplied variation scores from step 3

Question 12

step 6 in finding correlation

Answer 12

SSx/SSy=the sum of each squared variation score, both x and y.

Question 13

Coefficient of Determination (eta^2 for correlations)

Answer 13

Measure of proportion of variance of one factor (Y) that can be explained by a second factor (X)

Question 14

Covariance

Answer 14

The extent to which X and Y vary together, represented by the data points proximity to a regression line.

Question 15

Positive Correlation

Answer 15

As values of one factor increase, the values of the second factor also increase (r greater than zero, less than/equal to 1)

Question 16

negative correlation

Answer 16

As values of one factor increase, the values of the other factor decrease (r is less than zero but greater than/equal to -1)

Question 17

Pearson Product-moment correlation coefficient

Answer 17

a way to measure the direction and strength of a linear relationship between two interval/ratio factors)

Question 18

Pearson correlation coefficient (r) formula

Answer 18

r=sum of (Zx*Zy)/n-1

Question 19

Raw Score Pearson Correlation formula

Answer 19

r=SSxy/sqrt(SSx*SSy) (Covariance divide by the total variance)

Question 20

Restriction of Range

Answer 20

When we only look at one “section” of an entire sample, that particular section might actually have a different relationship to itself than it does to the rest of the entire sample/population; a correlation does not necessarily represent the entire population, and should only be compared within that context.

Question 21

Third Variable

Answer 21

A variable that is not X or Y but is also related to the correlation between X and Y (Summer is related to Ice Cream and Crime, though it does not cause the relationship)

Question 22

Reverse Causality

Answer 22

In correlation, the causes go both directions: worse mood may be caused by more eating, or more eating can be caused by worse mood.

Question 23

Systematic Causality

Answer 23

A feedback loop: the more we eat, the worse we feel, and thus the more we eat.

Question 24

Confound Variable

Answer 24

Changes in factors caused by a third variable not measured