Lecture 18-19

Question 1

Why does simple linear correlation not use an equation?

Answer 1

Due to no causal relationship

Question 2

How is the correlation between two variables measured?

Answer 2

By calculating the correlation coefficient (r)

Question 3

What is the correlation coefficient (r)?

Answer 3

It ranges from -1 to 1 where 1 = strong positive correlation, -1 = strong negative correlation, and 0 = no correlation

Question 4

What is the relationship between correlation and regression?

Answer 4

Regression is used when you have an independent/dependent relationship, correlation doesn’t and instead just tests if two variables are correlated

Question 5

What types of hypotheses are tested in simple linear correlation?

Answer 5

2-tailed = tests for a significant correlation and 1-tailed = tests for a (+/-) correlation

Question 6

What is the population parameter estimated by the sample statistic r?

Answer 6

p (rho)

Question 7

What is the Spearman rank correlation?

Answer 7

No parametric alternative test for associations for relationships between 2 ratio-interval scale variables when the normality assumptions aren’t met, can also test with ordinal-scale variable

Question 8

What hypotheses are used in the Spearman rank correlation?

Answer 8

Ps =/≠ 0 : no correlation or is one

Question 9

What is the degrees of freedom in the Spearman rank correlation?

Answer 9

DF = n