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Umnica [9.8K]
3 years ago
5

A researcher claims that the average body mass index (BMI) of adult Canadians is more than 25.0. He takes a SRS of 250 Canadians

and finds x = 26.3. The p-value for this test is 0.001. What is the best interpretation of this value?
Mathematics
1 answer:
Serjik [45]3 years ago
3 0

Answer:

The probability of obtaining a result equivalent to or greater than what was the truly observed value of the test statistic is 0.001.

Step-by-step explanation:

The researcher can use a one sample <em>z</em> test to determine whether his claim is correct or not.

The hypothesis to test whether the mean BMI is more than 25.0, is defined as:

<em>H₀</em>: The mean BMI is not more than 25.0, i.e. <em>μ </em>≤ 25.0.

<em>Hₐ</em>: The mean BMI is more than 25.0, i.e. <em>μ </em>> 25.0.

The test statistic is defined as:

z=\frac{\bar x-\mu}{\sigma/\sqrt{n}}

The <em>p</em>-value of the test is,

<em>p</em> = 0.001.

The p-value is well-defined as per the probability, [under the null-hypothesis (<em>H₀</em>)], of attaining a result equivalent to or greater than what was the truly observed value of the test statistic.

A small p-value (typically ≤ 0.05) specifies sufficient proof against the null hypothesis (<em>H₀</em>), so you discard <em>H₀</em>. A large p-value (> 0.05) specifies fragile proof against the <em>H₀</em>, so you fail to discard <em>H₀.</em>

The <em>p</em>-value of 0.001 indicates that the probability of obtaining a result equivalent to or greater than what was the truly observed value of the test statistic is 0.001.

As the <em>p</em>-value is very small, the null hypothesis will be rejected at any level of significance.

Thus, concluding that the mean BMI of adult Canadians is more than 25.0.

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