What is the goal of an independent-measures research study
To evaluate the mean difference between two populations
Independent measures t test (Between-groups designs) how many variables?
Every participant gets one independent variable
Repeated measures t test (Within-groups design) how many variables
Every participant would get all independent variables
For a within-subject design you should use a…?
Repeated measures design
Independent Samples
The observations should not be correlated between the two groups
The new t test for independent samples
t=(M1-M2) - (μ1- μ2)/SE for difference between sample means
-population=0
Assumptions for independent sample t statistics
1.)The observations within each sample must be independent
2.)Two populations from the samples must be normal
3.)Homogeneity of variance
Homogeneity of Variance
The variances of the populations are the same (SD^2 low 1=SD^2 low 2)
Hartley’s F-Max Test
It helps determines if homogeneity of variance has been satisfied
F-max= s^2 largest/s^2 smallest
What does the F-Max test consist of?
1.) Sample variance provides an unbiased estimate of the population variance
2.) Population variances are equal so the sample variances should be very similar
Null Hypothesis
There is no mean difference when comparing 2 variables
Alternative Hypothesis
There is a mean difference when comparing 2 variables
JASP APA tips
-Anything greater than 0.05m we fail to reject (p value)
-Reject/fail, t(df)=t, p=#
State Null Hypothesis for independent measures t test
-Population
-u1-u2=0
State Alternative Hypothesis for independent measures t test
-Population
-u1-u2 is not equal to 0
Pooled Variance
Combining the two sample variance into a single value
What language is used for a one tail hypothesis test?
More or less than when comparing two populations
Why do we calculate pooled variance?
When the variances of two different sample sizes are “equal” so we average the sample variance
