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A study on women’s weights was recently completed.

Fifteen randomly selected high school females from an urban setting were compared to $16$ randomly selected high school women from a rural setting. The results are below:

Two-Sample T for Urban Weights vs. Rural Weights

N Mean StDev SE Mean
Urban Weights 15 126.1 10.5 2.7
Rural Weights 16 128.8 13.2 3.3

$\text{Difference} = \mu _{\text{Urban Weights}} - \mu_{ \text{Rural Weights}}$

Estimate for difference: $-2.68$

$95\%$ CI for difference: ($-11.45, 6.09$)

T-test of difference = $0$ (vs. not =): T-value = $-0.63$, P-value = $0.537$, DF = $28$

What could be a possible way to reduce the probability of a type I error in this context?


Increase alpha level.


Decrease alpha level.


Decrease sample sizes.


Use a multi-stage sample.


Select from different areas across the country to reduce variability.

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