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19 Cards in this Set

  • Front
  • Back
background for hypothesis testing
1.expose participants to 2 or more levels of IV
2.determine size of f-ratio by comparing between and within group variance
3.set the cut-off for acceptable prob. that results are due to chance (alpha level)
4.calculate actual prob(p-value)
P-value less than Alpha level
prob that difference is due to chance is acceptable
Null hypothesis rejected
statistically significant difference b/w the groups
P-value more than alpha level
prob. that difference is due to chance is not acceptable
Null hypothesis is accepted
NOT statistically significatn
Null hypothesis
no difference between experimental and control groups in terms of DV

hypothesis of "no difference"

observed difference due to change, not IV
testing Null hypothesis
reject null when prob is small <.05

accept null when prob is large <.05
alternative hypothesis
2 groups are different in terms of DV
hypothesis of "differences exist"

observed difference due to IV (hopefully)

alt.rejected if null accepted
alt.accepted if null rejected
type I error
when reject Null, but shouldnt have

results say there is difference between groups..but difference is due to chance

prob of type I error=Alpha
setting smaller alpha
..and get significant results:
more confidence that difference not due to chance
if set larger alpha value
..and get significant results:
less confidence difference is not due to chance
=ability of a statistical test to detect a relationship between variables (corr) or differences between groups (exp) when they exist
power + alpha level
smaller alpha reduces power, bigger alpha increases power
requires more between-group variance to show a difference
usually experimenter will not set higher than 0.5
power + effect size
(overlap between populations)
larger(less overlap)=increases power
manipulate IV using extreme differences b/w levels to show a difference
potential solution: pilot study
power + within group variance
less within group variance increases power
reduce it by reducing reliabilty of DV, consistent treatment of participants
power + sample size
increasing sample size increases power
larger the sample,the more confident we can be that the result was not due to chance
determining power
can determine # of participants required to get statistically significant findings
use large samples
can test any number of groups simultaneously to look for a difference
Tests the Null that no difference among all possible pairings of groups A thru D simultaneously
test for differences between 1 pair of groups t a time
(ex. AandB, AandC, AandD..)
probability pyramiding
with 4 levels (6 possible pairings), prob of Type I error increases from 0.5 to 0.26
(26% differences due to chance)

with 3 levels, probability of Type I error increases from 0.5 to 0.14
"after the fact" test
tells which pairs of groups are statistically different