Stats Ch9 Definitions

T/F Standard error determines how much difference is reasonable to expect between pop mean and sample mean

T
Sample Variance formula

s2= SS/(n-1) = SS/df
sample standard deviation formula
- s=
- square root of SS/(n-1)
estimated standard error formula (used for t scores)

Sm = square root of s2/n
t score formula

t=M-m/Sm
T/F the greater the favlue of df for a sample, the better s2 represents o2; the better the t statistic approximates the z score.

t
T/F t distribution has the same shape as z

F: t is flatter and more variable than Z. Larger the df, the more closely T resembles Z
Cohen's D formula/estimated D formula

Cohen's D= mean difference/standard deviation (M-m/s)
r2 is the measure of effect size. Formula?

r2=t2/(t2+df)

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mangoboba

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Stats Ch9 Definitions

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ch9 definitions

Updated

2010-10-17T19:22:27Z

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