Answer:
Correct option is (C).
Step-by-step explanation:
The <em>p</em>-value is well defined as the probability, [under the null-hypothesis (H₀)], of attaining a result, of a statistical hypothesis test, equivalent to or greater than what was the truly observed.
A small <em>p</em>-value (typically ≤ 0.05) specifies solid proof against the null hypothesis (H₀), so you reject the null hypothesis.
A large <em>p</em>-value (> 0.05) specifies fragile proof against the H₀, so you fail to reject the null hypothesis.
A nutritionist is concerned that the true average calorie count in the french fries served by a fast-food restaurant is higher than 120 calories.
The hypothesis to test this can be defined as:
<em>H₀:</em><em> </em>The true average calorie count in the french fries is 120 calories, i.e. <em>μ</em> = 120.
<em>Hₐ:</em><em> </em>The true average calorie count in the french fries is more than 120 calories, i.e. <em>μ</em> > 120.
The test statistic is:
The sample mean calories in the sample of 35 small orders of french fries is,
And the <em>p</em>-value is,
<em>p</em>-value = 0.00093
The <em>p</em>-value can be interpreted as the probability of getting a sample of 155.6 calories or greater when the population mean is 120 calories.
That is,
The <em>p</em>-value can also be interpreted as probability of getting a sample of 84.4 calories or less when the population mean is 120 calories.
*
*Since the normal distribution is symmetric the P (Z < -z) = P (Z > z).
So,
Thus, the correct option is (C).
