Lecture 12 Flashcards
Categorical Variable
Nominal–categories the sample distinctly falls into
Continuous Variable
Interval–a variable that can be measured to any level of precision
Dependent Variable
Outcome Variable
A Variable whose measure is based on the manipulation of the predictor (IV) variable
Independent Variable
Predictor Variable
A variable that is manipulated in order to make changes on the outcome (DV) variable
MATCHED SAMPLES
Looking at two samples, in a group or in two points in time.
Standard Error of difference between means
LOOKIT UP
When would you conduct a one-sample t-test?
*Used to compare the sample mean of a variable (DV) with a “test value”
Example: Determine if depression is more/less apparent in teenage boys who play sports, using a standardized test called the KUDI.
You test 30 subjects, and compare their outcome sample mean to the standardized score set for teenage boys.
When would you conduct a paired-samples t-test?
- Used to compare means of a single sample in a longitudinal design with only two time points (e.g., pre and post test).
- Can be used to compare the means of two variables (e.g. depression and quality of life).
When would you conduct an independent-samples t-test?
*Used to compare the means of two independent samples (a subject cannot be in both groups) on a given variable
Requirements of IV and DV in an independent-sample t-test
- One categorical/nominal IV, with two levels or groups
* One continuous/interval/ratio DV
What is the null hypothesis for all the types of sampled t-tests?
The mean difference between the two comparison groups = 0
What is the null hyp for Levene’s test of the equality (of error) variances?
It evaluates the variance between the groups to ensure the assumption of homogeneity of variances.
Ho = Xa = Xb
What if the outcome of the null hyp for Levene’s test is not significant?
If it is not significant, then we assume that we have equal variances.
**If p > .05, accept the null
What if the outcome of the null hyp for Levene’s test IS significant?
If it is significant, we MAY NOT assume that we have equal variances.
**If p
If given a 95% confidence interval around two group means for an independent-samples t test, be able to
test the null hypothesis that the mean difference between two group means is zero (or that the two group means are equal).
- Examine Levene’s test for equality of variances
* *SPSS finds it for you, along with the F-value.
* * Find the p- value (also 1 - F)
* *Compare p-value with .05…is is significant or not? - Depending on if it is significant or not, use the corresponding data in the SPSS output chart.
- Looking at the CI values, determine if 0 would fall in that range.
* *If 0 is present, you fail to reject the null, because the difference between the two means is not significantly different from 0