Exam 2 Flashcards
What is a measure of linear association between two continuous variables.
Bivariate correlation
What determines the intensity of the correlation?
Strength
What are the directions of a correlation?
- Positive
- Negative
- No correlation
What direction does a positive correlation do?
Both up
What direction does a negative correlation go?
Both go down
_____ is a random association.
No correlation
______ is a statistical method to predict the criterion, outcome, or dependent variable, from a single predictor or independent variable.
Linear Regression
What are the four types of analysis?
- Chi square
- Independent t-test
- Dependent t-test
- ANOVA
Which test is needed?
“Is there a difference between genders and the type of exercise”
Chi square
Which test is needed?
“Is there a difference in pre season and postseason run time for CSUSB Womens track team”
Dependent t-test
Which test is needed?
“Does burnout level differ among competition level (recreational, collegiate, professional)”.
ANOVA
Which test is needed?
“Differences in girls and boys BMI”
Independent t-test
In correlations, what is the p value labeled as?
Significance
If you are given:
IV: 1 nominal (pre & post)
DV: 1 continuous
What test are you using?
Dependent T-test
If you are given:
IV: 1 nominal
DV: 1 nominal
What test are you running?
Chi Square
If you are given:
IV: 1 nominal (2 groups)
DV: 1 continuous
Independent T-test
If you are given:
IV: 1 nominal (> 2 groups)
DV: 1 continuous
ANOVA
If you are running a independent t-test about differences in boys and girls BMI, and you receive a significance value of 0.00, what are you doing with that information?
Rejecting the null and stating that their is a difference in BMI and genders
If you are running a dependent t-test about pre season and post season miles times for CSUSB Womens track, and you receive a significance value of 0.51, what are you doing with this info?
Accepting the null and concluding that there is no difference between pre & post season mile times.
PRACTICE the correlation formula
Chapter 11 Slides
Ok.
PRACTICE linear regression
Ok.
