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Independent samples t-test
To compare means of two separate samples
Independent samples t-test is a ______ subjects design
Between
Independent samples t-test formula for t
Pros of between subjects design
Prevents carryover effects
Prevents burnout (shorter duration)
Cons of between subject design
larger samples needed for sufficient power
More resources
Individual differences
To compare an experimental and a control group, you would use a(n) ________.
Independent samples t-test
Degrees of freedom
The number of scores in a sample that are free to vary once a mean is known
How do df effect the distribution of t?
Large df: normal distribution
Small df: flatter curve (requires a larger OV, punishes small samples)
Effect size
Measure of the mean difference in terms of standard deviations between the raw scores
_____ is a small effect
0-0.2
_____ is a medium effect
0.2-0.5
_____ is a large effect
0.5+
Independent samples t-test effect size formula
How is t reported in APA?
t(df) = OV, p ___ .05
Independent samples t-test df formula
Statistical power
Probability that a test will correctly reject a false null
How can statistical power be increased?
increase effect size
Increase sample size
Increase alpha level
Use a one-tailed test
Dependent samples t-test
To compare means from testing the same sample more than once
Dependent samples t-test aka
Repeated measures design
Within subjects design
Within subjects design pros
need fewer participants to get the same df/power
Each participant acts as their own control
Within subjects design cons
order/learning effects
May increase potential for alternative explanations
Dependent samples formula for t
(T/F): dependent and independent sample t-tests use different t-tables to determine the critical value.
False, it is the same t-table
ANOVA
Analysis of variance
Based on sources of variation rather than mean differences
Factor
The independent variable that designates the groups to be compared in ANOVA
Level
Different groups within a factor
What is the goal of the ANOVA formula?
Divide out differences due to chance in order to isolate the treatment effect
Between groups variance reflects differences due to ________
Treatment effects
Chance, error, etc.
Within groups variance reflects differences due to ______
Chance, error, etc.
The larger the F value, the ______ the p value
Smaller
Sum of squares between
Sum of squares within formula
Variance ______ groups / variance _____ groups
Between / within
Omnibus test
Identifies that there is a difference between groups, but not which groups
Which test is an omnibus test?
F-test, ANOVA
ANOVA numerator df formula
k - 1
ANOVA denominator df formula
N - k
What is k?
The number of levels
N vs n
Total sample size vs group sample size
Carryover effects
If a dependent sample is given the treatment before tested for control, than the treatment effects may carryover into the control measurement.
Maturation effects
With a dependent sample, natural life development/maturation may confound treatment effects if they are measured with considerable time between
Order/learning effects
Participants in a dependent sample may learn from the first testing, enhancing performance on the second testing
Note
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