Questions: QUESTION 10 The bottom line in terms of evaluating the P-Value to determine the outcome of a Hypothesis test: a. is to use the P-value to determine the probability of making a Type-I Error b. is to use the P-value to determine the probability of making a Type-II Error c. is to accept the H1 (alternative hypothesis) if the P-Value is greater than 1 d. is to reject the Ho (null hypothesis) if the P-Value < alpha (alpha)

QUESTION 10

The bottom line in terms of evaluating the P-Value to determine the outcome of a Hypothesis test:
a. is to use the P-value to determine the probability of making a Type-I Error
b. is to use the P-value to determine the probability of making a Type-II Error
c. is to accept the H1 (alternative hypothesis) if the P-Value is greater than 1
d. is to reject the Ho (null hypothesis) if the P-Value < alpha (alpha)

Transcript text: QUESTION 10 The bottom line in terms of evaluating the P-Value to determine the outcome of a Hypothesis test: a. is to use the $P$-value to determine the probability of making a Type-I Error b. is to use the P -value to determine the probability of making a Type-II Error c. is to accept the H 1 (alternative hypothesis) if the P -Value is greater than 1 d. is to reject the Ho (null hypothesis) if the $P$-Value < $\alpha$ (alpha)

Solution

Solution Steps

Step 1: Understanding the P-Value

The P-Value is a statistical measure that helps determine the strength of the evidence against the null hypothesis ($H_0$). It represents the probability of observing the test results, or something more extreme, assuming that the null hypothesis is true.

Step 2: Evaluating the Options

Let's evaluate each option based on the definition and use of the P-Value:

Option a: "is to use the P-value to determine the probability of making a Type-I Error"
This is incorrect. The P-Value itself is not the probability of making a Type-I Error. The probability of making a Type-I Error is determined by the significance level ($\alpha$), not the P-Value.
Option b: "is to use the P-value to determine the probability of making a Type-II Error"
This is incorrect. The P-Value does not provide information about the probability of making a Type-II Error. The Type-II Error is related to the power of the test, which is not directly determined by the P-Value.
Option c: "is to accept the H1 (alternative hypothesis) if the P-Value is greater than 1"
This is incorrect. The P-Value cannot be greater than 1, as it represents a probability. Therefore, this option is not valid.
Option d: "is to reject the Ho (null hypothesis) if the P-Value < $\alpha$ (alpha)"
This is correct. If the P-Value is less than the significance level ($\alpha$), it indicates that the observed data is unlikely under the null hypothesis, and we reject the null hypothesis.