2 T Test
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By selecting a smaller alpha level, a researcher is

The z score boundaries for a critical region are determined by
the alpha level

Two possible ways of comparing two samples means
 The two means could come from two completely separate groups of participants
 Two sets of data could be gathered from the same group

Independent Measures ttest
 Two separate groups being tested
 Also known as between subjects design

t formula
[(M1M2)(u1u2)]/S(M1M2)

s_{(M}_{1M2)}_{=}
sqrt[(s1^{2}/n1)+(s2^{2/}n2)]

Estimated standard error is only true if
both ns are the same

Pooled variance formula
Pooled variance formula with standard error
see card

H0 and H1 for two independent sample means
u1u2=0

We use the sample mean difference to
Estimate the population mean difference

Condfidence interval for two independent sample means formula
u1u2=M1M2+t*S_{M1M2}

Twotailed hypothesis
H_{o}
H_{1}
 u_{1}u_{2=}0
 u_{1}u_{2}does not equal 0

Onetailed (uppertail critical)
HO
H1
see formula sheet

Onetailed (lowertail critical)
see formula sheet

3 Assumptions of t tests
 Observations within each sample must be independent
 The population from which the samples are selected must be approximately normal
 The two populations from which samples are selected must have the same variance

Hartley Fmax test
Tests?
1.2.3.
Tests whether our sample variances are reasonably close
 1. Compute sample variance for each sample
 2. Select largest and smallest of these variances and compute s2(largest)/s2(smallest) to get F max
 3.Compare Fmax value with the critical value