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Chapter 8: Q. 9.48 (page 370)

What is the P-value of a hypothesis test? When does it provide evidence against the null hypothesis?

Short Answer

Expert verified

P-value is the probability of observing a value of the test statistics as extreme as or more extreme than that observed, under the assumption that null hypothesis is true.

Small P-values provide evidence against null hypothesis test.

Step by step solution

01

Step 1. Given information

Hypothesis testing is an act in statistics whereby an analyst tests an assumption regarding a population parameter.

02

Step 2. Explanation

P-value is the probability of observing a value of the test statistics as extreme as or more extreme than that observed, under the assumption that null hypothesis is true.

The P-value can be interpreted as the observed significance level of a hypothesis test.

Small P-values provide evidence against null hypothesis test.

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Most popular questions from this chapter

Final Conclusions. In Exercises 25–28, use a significance level of α= 0.05 and use the given information for the following:

a. State a conclusion about the null hypothesis. (Reject H0 or fail to reject H0.)

b. Without using technical terms or symbols, state a final conclusion that addresses the original claim.

Original claim: The mean pulse rate (in beats per minute) of adult males is 72 bpm. The hypothesis test results in a P-value of 0.0095.

Using Technology. In Exercises 5–8, identify the indicated values or interpret the given display. Use the normal distribution as an approximation to the binomial distribution, as described in Part 1 of this section. Use = 0.05 significance level and answer the following:

a. Is the test two-tailed, left-tailed, or right-tailed?

b. What is the test statistic?

c. What is the P-value?

d. What is the null hypothesis, and what do you conclude about it?

e. What is the final conclusion?

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a. Express the original claim in symbolic form.

b. Identify the null and alternative hypotheses.

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In Exercises 9–12, refer to the exercise identified. Make subjective estimates to decide whether results are significantly low or significantly high, then state a conclusion about the original claim. For example, if the claim is that a coin favours heads and sample results consist of 11 heads in 20 flips, conclude that there is not sufficient evidence to support the claim that the coin favours heads (because it is easy to get 11 heads in 20 flips by chance with a fair coin).

Exercise 5 “Online Data”

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