Lecture 9

Question 1

Lecture 9:

What is a Correlation Coefficient?

Answer 1

Measures the extent to which 2 variables are related
- sometimes called a bivariate correlation
- tells us the magnitude & direction of relationship
- only appropriate for linear relationships

Question 2

Lecture 9:

What are correlations useful?

Answer 2

They allow us to predict values for 1 variable based on a known value of the other

Question 3

Lecture 9:

What is a Correlation?

Answer 3

The extent to which the direction & size of deviations from the mean in one variable (group 1) are related to the direction & size of deviations from the mean in another variable (group 2)

Question 4

Lecture 9:

What is a Positive Correlation?
- give example

Answer 4

Includes subjects who score above mean on X score, above mean on Y score, & vice versa
- eg; power clean & vertical jump

Line of best fit extends from bottom left to top right

Question 5

Lecture 9:

What is a Negative Correlation?

Answer 5

Includes subjects who score below mean on X score & above mean on Y score, & vice versa
- eg; vertical jump & 40-yard dash time
- eg; long run time vs short jump

Question 6

Lecture 9:

What are the Pearson r value ranges?
(Pearson product moment correlation coefficient = r)

Answer 6

Pearson r values range from -1.00 to +1.00
*the closer the r is to -1.00 or +1.00, the stringer the relationship

Question 7

Lecture 9:

What does a Pearson r value of 0 mean?

Answer 7

There is no relationship between the variables

Question 8

Lecture 9:

What r value would you expect for the relationship of team cohesion & performance?

Answer 8

Positive with r of about 0.4

Question 9

Lecture 9:

What r value would you expect for the relationship of 10km run time and VO2 max?

Answer 9

Negative & r value of about -0.9 because as VO2max increases, run time decreases

Question 10

Lecture 9:

Review slide 13!!!!!

Answer 10

Relationships & calculating r values

Question 11

Lecture 9:

When interpreting general coefficient values; what would you interpret from a correlation size of 0.8-1.0?

Answer 11

A very strong relationship (eg; seen in engineering)

Question 12

Lecture 9:

When interpreting general coefficient values; what would you interpret from a correlation size of 0.6-0.8?

Answer 12

A strong relationship can be interpreted

Question 13

Lecture 9:

When interpreting general coefficient values; what would you interpret from a correlation size of 0.4-0.6?

Answer 13

A moderate relationship can be interpreted as

Question 14

Lectrue 9:

How do you determine if r is statistically significant?

Answer 14

if r = 0 than no relationship between the variables but if r does not = 0 than there is a relationship between the variable

Question 15

Lecture 9:

What 3 pieces of information are needed to determine the statistical significance of your r value & study?

Answer 15

1.) correlation value (r = …)
2.) the # of pairs of observations (degrees of freedom = df)
3.) our alpha value (threshold of significance, a = 0.05)
*compare these values of Table A.2 chart

Question 16

Lecture 9:

If r critical is less than r, what hypothesis do you reject & which do you support?

Answer 16

If r critical < r, reject null hypothesis and support real one as ther is a statistically significant correlation/relationship between the variables

Question 17

Lecture 9:

What is the coefficient of determination when discussing correlations?

Answer 17

The percentage of variance in 1 variable that is accounted for by the variance in the other variable

Question 18

Lecture 9:

How do you find the correlation coefficient (r^2)?

Answer 18

Eg; if r = .891, then r^2 = .794 = 79%
- meaning… 79% of variance can be explained & 21% of the variance cannot be explained

Question 19

Lecture 9:

How are correlation & varience related?

Answer 19

The stronger the correlation, the more varience can be explained (higher %)