When calculating the P-value, must you change the sign of the test statistic?

In summary, when calculating the P-value, you must change the sign of the test statistic depending on the type of test (lower, upper). This means that for a lower-tailed test, the answer should be the cumulative probability of the negative value of the test statistic, and for an upper-tailed test, the answer should be the complement of the cumulative probability of the positive value of the test statistic. This may differ from what is seen in some textbooks, but it is the correct method.
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Homework Statement


When calculating the P-value, must you change the sign of the test statistic depending on the type of test (lower, upper)?

For example, if your calculated test statistic is t=2.5 and you want to perform a lower-tailed test, is your answer the cumulative probability of 2.5 or -2.5?

I ask because there are no similar examples in my textbook. All the problems for lower-tailed tests use negative test statistic values, and all the problems for upper-tailed tests use positive test statistic values.

There is one odd-numbered problem asking for an upper tailed test with z= -2.2, and the answer is given as the complement of the cumulative probability of -2.2. since this is the only problem like this given, I don't know if it is right or not.

Because if so, then I get answers such as 0.9983 for the P-value.

Thanks.
 
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Homework Equations The Attempt at a Solution Yes, you must change the sign of the test statistic depending on the type of test (lower, upper). If you want to perform a lower-tailed test, your answer should be the cumulative probability of -2.5. The problem with an upper tailed test with z = -2.2 is correct and the P-value should be 0.9983.
 

1. What is a P-value and why is it important in statistical analysis?

A P-value, or probability value, is a measure of the likelihood that the observed results of a study could have occurred by chance. It is important in statistical analysis as it helps determine the statistical significance of a study's findings.

2. How is the P-value calculated?

The P-value is calculated by comparing the observed test statistic to the expected distribution of the test statistic under the null hypothesis. This is typically done using a statistical software or by referring to a statistical table.

3. What is the significance level and how does it relate to the P-value?

The significance level, often denoted as alpha (α), is the threshold at which a P-value is considered statistically significant. It is typically set at 0.05 or 0.01. If the P-value is less than or equal to the significance level, the results are considered statistically significant.

4. Do you need to change the sign of the test statistic when calculating the P-value?

Yes, when calculating the P-value, the sign of the test statistic must be changed if it is a two-tailed test. This is because the P-value is calculated based on the area under the curve of the test statistic distribution, which is symmetrical. For a one-tailed test, the sign of the test statistic does not need to be changed.

5. Can the P-value alone determine the significance of a study's findings?

No, the P-value should not be the only factor used to determine the significance of a study's findings. Other factors such as effect size, confidence intervals, and the study's design and methods should also be considered. Additionally, the P-value should not be interpreted in isolation and should always be considered in the context of the research question and study objectives.

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