Task 5 Flashcards
The samples in ANOVA are
a) dependent
b) independent
independent
In ANOVA normality is assumed, true or false?
true
How can we assume normality?
basic check - histogram
What to do if normality is violated
ensure samples are “large enough” -> CLT
Do we assume equal variances?
Yes
How do we check for equal variances?
Levene’s test
What to do if equal variances assumption is violated?
ensure sample size are “equally large”
Sum of squares?
a) SSG
b) SSW
c) SST
variation
a) between groups
b) within groups
c) total
Mean square?
average variation (variance)
Which sum of squares is for taking error into account?
SSW
Which df takes into df of erro?
DFW
What is a p-value in relation to ANOVA?
the probability of the F calculated or an even larger one if Ho is true
What does a one-way ANOVA enable us to compare?
2 or more independent samples
What is the general ANOVA model?
Yij = μ + ai + Eij
Yij: the individual score of a person j in group i
μ: the effect of constant factors (they are the same in every condition- its what all 3 samples have in common)
ai: the effect of the research factor (independent variable) e.g. no effect ai=0, increase in sales ai=+1
- > to calcualte group effect a1 = μ - ui (ui is the group mean)
Eij: the effect of remaining factors/effect of chance or individual differences aka “error” as they are not explicitly measured
-> to calculate Eij = Yij - ui (ui is the group mean)
The sum of all ai’s always equals
0
The sum of all Eij’s always equals
0
How to calculate how much one person deviates in a population?
Yij - μ
What acts as explained and unexplained variation?
explained - SSG
unexplained - SSW
What is the Ho?
u1=u2=u3 (i.e. no group effect e.g. no influence on advertising)
What is the Ha?
Not all u’s equal
Does accepting Ha mean there is definitely effect from the dependent variable?
No there may be the effect of chance or error
How can we determine normality? (only need to know about histograms)
Explore output
- Skewness = 0 if normal
- > rule of thumb: the skewness of the sample can lie within -1 and +1 to e considered normal
- > positive means skewed right and vice versa - Kurtosis (flatess) = 0 if normal
- > same rule of theumb
- > positive means high point and vice versa
What is always an unbiased estimator of the so-called error variance?
the variance within a group (MSW) is an unbiased estimator of error variance: the dispersion in the population due to remaining factors
What is s^2p equal to in anova?
MSW
