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How to Determine a p-Value When Testing a Null Hypothesis

Sample question: A researcher claims that more than 23% of community members go to church regularly. In a recent survey, 126 out of 420 people stated they went to church regularly. Is there enough evidence at α = 0.05 to support this claim? Use the P-Value method to support or reject null hypothesis.

The ANOVA test procedure produces an F-statistic, which is used to calculate the p-value.

Step 4. Find the appropriate critical values for the tests using the Z-table for test of one proportion, or the t-table if a test for one mean. REMEMBER: for the one mean test the degrees for freedom are the sample size minus one (i.e. n - 1). Write down clearly the rejection region for the problem.

To find thevalue for your test statistic:

Click the link the skip to the situation you need to support or reject null hypothesis for:

We have already seen how to do the first step, and have null and alternate hypotheses. The second step involves the calculation of the t-statistic for one mean, using the formula:

For the third step, we need a table of tabulated t-values for significance level and degrees of freedom, such as the one found in your lab manual or most statistics textbooks. Referring to a table for a 95% confidence limit for a 1-tailed test, we find tν=6,95% = 1.94. (The difference between was covered in a previous section.)

Use the following formula to calculate your test value.

Rejection region: the set of values for the test statistic that leads to rejection of Ho.

Hello, thanks for the videos it is very illustrative, but i have one question i dont understand, why we reject the null hypothesis when the p value less than .05?

If your P value is less than the chosen significance level then you reject the null hypothesis i.e. accept that your sample gives reasonable evidence to support the alternative hypothesis. It does NOT imply a "meaningful" or "important" difference; that is for you to decide when considering the real-world relevance of your result.

Step 3. Compute the value of the test statistic:
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Use the following formula to calculate your test value.

There are two approaches for making a statistical decision regarding a null hypothesis. One is the rejection region approach and the second is the p-value (or probability value) approach. Of the two methods, the latter is more commonly used and provided in published literature. However, understanding the rejection region approach can go a long way in one's understanding of the p-value method. Regardless of method applied, the conclusions from the two approaches are exactly the same. In explaining these processes in this section of the lesson, we will build upon the prior steps already discussed (i.e. setting up hypotheses, stating the level of significance α, and calculating the appropriate test statistic).

Step 3. Compute the value of the test statistic:

Let's start out here by having Dr. Wiesner walk through a comparison of the p-value approach with the rejection region approach to hypothesis testing.

P-Value in Statistical Hypothesis Tests: What is it?

Find the . We’re dealing with a population, so the critical value is a .
Use the following formula to find the .

How to Determine a p-Value When Testing a Null Hypothesis

Find the by looking up your answer from step 3 in the . To get the p-value, subtract the area from 1. For example, if your area is .990 then your p-value is 1-.9950 = 0.005. Note: for a two-tailed test, you’ll need to halve this amount to get the p-value in one tail.

Do you reject the null hypothesis when $p < lpha$ or $p ..

Compare your answer from step 4 with the α value given in the question. Should you support or reject the null hypothesis?
If step 7 is less than or equal to α, reject the null hypothesis, otherwise do not reject it.

Decide to either reject the null hypothesis in favor of the ..

The term significance level (alpha) is used to refer to a pre-chosen probability and the term "P value" is used to indicate a probability that you calculate after a given study.

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