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Statistics: Interpreting Different Results of Hypothesis Testing

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I need help with the following question regarding the interpretation of hypothesis testing:

A public health researcher tested the hypothesis that providing new car buyers with child safety seats will also act as an incentive for parents to take other measures to protect their children (such as driving more safely, child-proofing the home, etc.). Dr. Joy counted all the occurrences of safe behaviors in the cars and homes of the parents who accepted the seats versus those who did not. The study found a significant difference at the .013 levels.

Another researcher did exactly the same study, and for our purposes, let's assume that everything was the same - same type of sample, same outcome measures, same car seats, and so on. Dr. Keel's results were marginally significant at the .051 level. Whose results do you trust more and why?

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Hi there,

Thanks for letting me work on your post. Here is my explanation:

A significant difference at the 0.013 ...

Solution Summary

The expert interprets different results of hypothesis testing.