5 - Comparing 2 samples Flashcards
What is the Central Limit Theorem?
“the sum of a large number of independent and
identically-distributed random variables will be
approximately normally distributed”
Which test would you do for two samples which:
a) Parametric (normally distributed) and not paired
b) Parametric and paired
c) Non-parametric and not paired
d) Non-parametric and paired
a) t-test
b) paired t-test
c) Mann-Whitney
d) Wilcoxon
t-test: for two unmatched \_\_\_\_\_\_ random samples assumes \_\_\_\_\_\_ distribution of residuals assumes \_\_\_\_\_ variances data should be continuous/discontin? (or nearly so) tests for difference in \_\_\_\_\_ special case of \_\_\_\_\_
t-test
for two unmatched independent random samples
assumes normal distribution of residuals
assumes equal variances
data should be continuous (or nearly so)
tests for difference in mean
special case of one-way ANOVA (next lecture)
Mann-Whitney U-test for two unmatched \_\_\_\_\_ random samples distribution\_\_\_\_\_\_\_\_ for both samples data does OR does not need to be continuous? tests for difference in \_\_\_\_\_ numbers are \_\_\_\_\_
Mann-Whitney U-test
for two unmatched independent random samples
any distribution ok, but same for both samples
data do not need to be continuous
tests for difference in median
numbers are ranked
Give some examples of matched pairs
in this instance what would you calculate?
left arm and right arm of patients before and after a treatment amount of time spent in choice of two areas by individual animal Calculate the difference
How do you calculate t?
(mean-specified value) / (Standard dev / sqrt of sample size)
paired t-test for two \_\_\_\_\_ samples assumes \_\_\_\_ distribution of residuals assumes \_\_\_\_ variances data should be \_\_\_\_\_\_ tests for \_\_\_\_\_\_ difference not equal to zero
paired t-test for two paired samples assumes normal distribution of residuals assumes equal variances data should be continuous (or nearly so) tests for mean pair difference not equal to zero