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chap 12: Analysis of Variance - Coggle Diagram
chap 12: Analysis of Variance
the variable (independent) that designates the groups being compared is called
factor
individual conditions or values that make up a factor are called the
levels
of the factor
a study combines two factors is called a
two-factor design or a factorial design
single-factor designs
3 samples of participants are selected
concerns about Type I errors
testwise alpha level
experimentwise alpha level
error term
ANOVA is similar to the t statisitics
want to compare differences among two or more sample means
F-ratio:
between vs within treatments variance
heart of ANOVA
between treatment simply measures how much difference exists between the treatment conditions
within treatment provides a measure of how big the differences are when H0 is true
the letter K is used to identify the number of treatment conditions
first need to compute a total sum of squares
then find degrees of freedom
next step is in the ANOVA procedure to compute the variance
use mean square or simply MS
need distribution of F-ratios
post hoc tests (or posttests) are additional hypothesis test that are done after an ANOVA to determine the mean differences
pariwise comparisons
Tukey's HSD test
Scheffe test
