Hi! im quite confused on this. can someone please help me? ill give brainiest if youre correct :)
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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:
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.