Week 5 - Statisitical Modes ANOVA & Non Parametric Alt Flashcards
The key ANOVA estimate is the F
F =
= (model variance) / (error
Remember, error variance often referred to as …..
residuals.
The larger the F , the more variance you are explaining in your DV by
your IV, as compared to error (although, F is not a direct measure of
effect size).
True or False
True
The larger the value of F the more evidence we have against the null
hypothesis.
True or False
True
You can only run post-doc tests if you F is statically significant (p<.05 if
you have a standard alpha of 0.05).
True or False
True
What does monotonic mean?
If you order pairs of data, the data constantly increase or consistently decrease
What are the assumptions of Spearman correlation?
At least one variable needs to be continuous.
The other variable can be continuous or dichotomous.
The relationship between the two variables is monotonic.
When do we run a Wilcoxon test?
When we want to compare two groups and out DV is non-parametric/not normally distributed. It’s a non-parametric version of a t-test.
What is a between-subjects Wilcoxon test called?
Mann-Whitney U Wilcoxon
A p -value less than 0.05 (typically ≤ 0.05) is statistically significant.
True or False
True
The most common threshold is p < 0.05, which means that the data is likely to occur less than 5% of the time under the null hypothesis.
True or False
True
When the p-value falls below the chosen alpha value, then we say the result of the test is statistically significant.
True or False
True
What three factors affect statistical power?
a.
Sample size, effect size, independence
b.
Sample size, effect size, type 1 error rate
c.
Sample size, statistical significance, type 1 error rate
d.
Sample size, statistical significance, independence
(b) Sample size, effect size, type 1 error rate
Data = x + y, where x and y are…
a.
Model and error
b.
Variance and distribution
c.
Distribution and model
d.
Variance and error
(a) model and error
The probability (p) value is…
a.
The probability of the null hypothesis being true
b.
Under the assumption that the null hypothesis is true, the probability of getting a sample as or more extreme as our own
c.
The probability that you are making the wrong decision
d.
The probably that if you ran the study again, you would obtain the same result that % of the time
b.
Under the assumption that the null hypothesis is true, the probability of getting a sample as or more extreme as our own
