Hypothesis Testing - Statistics How To

Krista,
I’m not sure what your question is. You list quite a few (identify null, alternate, test status, p-value or critical). Are you having trouble identifying the null and alternate hypotheses? Or is it that you don’t know what test to run?
BTW: both the critical value and p-value will give you the same results. I’d just choose one and go from there.
Stephanie

Type I and type II errors - Wikipedia

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THE LEVERAGE EFFECT AND THE ASYMMETRY OF …

The null hypothesis is essentially the "devil's advocate" position. That is, it assumes that whatever you are trying to prove did not happen (hint: it usually states that something equals zero). For example, the two different teaching methods did not result in different exam performances (i.e., zero difference). Another example might be that there is no relationship between anxiety and athletic performance (i.e., the slope is zero). The alternative hypothesis states the opposite and is usually the hypothesis you are trying to prove (e.g., the two different teaching methods did result in different exam performances). Initially, you can state these hypotheses in more general terms (e.g., using terms like "effect", "relationship", etc.), as shown below for the teaching methods example:

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So, you might get a p-value such as 0.03 (i.e., p = .03). This means that there is a 3% chance of finding a difference as large as (or larger than) the one in your study given that the null hypothesis is true. However, you want to know whether this is "statistically significant". Typically, if there was a 5% or less chance (5 times in 100 or less) that the difference in the mean exam performance between the two teaching methods (or whatever statistic you are using) is as different as observed given the null hypothesis is true, you would reject the null hypothesis and accept the alternative hypothesis. Alternately, if the chance was greater than 5% (5 times in 100 or more), you would fail to reject the null hypothesis and would not accept the alternative hypothesis. As such, in this example where p = .03, we would reject the null hypothesis and accept the alternative hypothesis. We reject it because at a significance level of 0.03 (i.e., less than a 5% chance), the result we obtained could happen too frequently for us to be confident that it was the two teaching methods that had an effect on exam performance.

20/10/1989 · University of Campinas, Rua Sérgio Buarque de Holanda, 651, Distr
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a significant p-value when the null hypothesis is ..

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would be equal to or more extreme than its observed value

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of your results under the null hypothesis