Correlation

Question 1

Both variables have to be continuous. T or F?

Answer 1

True

Question 2

Interpret this:

r(10)=.667, p=.018

Answer 2

r: inferential statistic
10: degrees of freedom (df); # of pairs-2
.667: r value
.018: p value

Question 3

Example of positive relationships?

Answer 3

As x increases, so does y

Ex: as education increases, so does earnings

Question 4

Example of negative relationships?

Answer 4

Inverse; as x goes up, y goes down

Ex: as self esteem goes up, depression goes down

Question 5

What describes a relationship?

Answer 5

• direction (positive or negative)
• strength (strong or weak)
• shape (linear or non linear)

Question 6

Correlation=causation. T or F?

Answer 6

False; it inly suggests relationships

• need more info to determine causality
• cause and effect can be indirect die to confounding variables

Question 7

Exakples of continuous variables tested together?

Answer 7

• IQ and yrs. of schooling
• height and weight
• # of days at gym per week and BMI
• depression and anxiety score
• # of children under age 18 in a family and annual family income

Question 8

What’s the null hypothesis?

Answer 8

There is no linear relationship between the 2 variables

Question 9

Reject the null hypothesis?

Answer 9

The 2 variables are related

Question 10

Fail to reject the null hypothesis?

Answer 10

The 2 variables aren’t related