chapter 3 Flashcards
1
Q
publication bias
A
- the bias that journals mainly (90%) publish studies with significant differences only
2
Q
p hacking and harking
A
- cherry picking data that is shared/selective reporting
- Hypothesizing after results are known
- not controlling type 1 error rate
3
Q
researcher degrees of freedom
A
ways a researcher can influence the p value
4
Q
acronym for addressing problems w NHST
A
- Effect size
- Meta analysis
- Bayesien Estimation
- Registration
- Sense
5
Q
wilcoxon rank sum test
A
does not assume normality and is used for comparing two independent groups.
6
Q
what is the reason for a post hoc test
A
- performed after ANOVA
- used to give more results that ANOVA does not cover
- ex. fishers LSD, tukey, etc.
7
Q
mean square formula
A
SS/df
8
Q
what do you typically want to be smaller, between or within variance
A
between should be larger than within (makes samples more independent of one another)
9
Q
bonferroni
A
- one of the most conservative tests
- partitioning the p-value acorss all tests
- ie if you have more than 2 samples, split the p value between then so it is still 0.05 when all tests are combined
- used as an alternative to ANOVA if you dont want to look at all the variables
10
Q
what do r=0.1, r=0.3, and r=0.5 mean
A
- 0.1= small effect, it accounts for 1% of variance
- 0.3= med effect, it accounts for 9% of variance
-0.5= large effect, it accounts for 25% of variance
11
Q
t or f: in a pearsons r the r scores are measured on a linear scale
A
false
12
Q
odds ratio formula
A
odds= p(event)/p(noevent)
13
Q
A