T-Test and Anova Flashcards
If 2 sets of data are completely separate, what would we do to compare them?
- Complete a Spearman (p) correlation or Pearson(r) correlation to see if they are RELATED positively or negatively
- Determine the coefficient of determination by squaring the correlation (p^2 or r^2)
If 2 sets of data are of the same parameter but for 2 independent groups, what would we do to compare them?
Conduct an independent t-test to determine if there is a significant difference between the means of the groups
If 2 sets of data are dependent and represent the same subjects in a pre-test/post-test scenario, what would we do to compare them?
Conduct a dependent t-test to determine if there is a significant difference between the means of the pre and post test
What is the t-test?
the statistical test to determine if there is a real difference between the means of 2 sets of scores
What is the Null Hypothesis (Ho)?
- a statement that indicates that for the 2 sets of scores, the means for the test are pretty well the same
- no significant difference between the means
When would we accept the null hypothesis?
- when there is no significant difference
- if the t-test value is less than the critical value from the table value
When would we reject the null hypothesis?
- when there is a significant difference in the means
- if the t-test value is greater than the critical value from the table value
Rejecting the null hypothesis is the same as …
accepting the alternative hypothesis (Hl)
What is the level of significance?
the probability of rejecting the null hypothesis when it is true
The most common levels of significance are…
.05 or .01
A .05 level of significance means that…
- there is a 5% chance that you are rejecting the null hypothesis when it is true
- there is a 5% chance that our conclusion will be wrong
Typically, we use what level of significance for physical education?
- p = 0.05
- maybe p = 0.01 but not that common
What is the degrees of freedom?
the number of values that are free to vary in a distribution so that the mean is the same
How is the degrees of freedom calculated in independent samples?
df = n1 + n2 -1
How is the degrees of freedom calculated in dependent samples?
df = N - 1