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Lesson 4 of 13

p-Value in Hypothesis Testing

The p-value is the probability, computed using the test statistic, that measures the support (or lack of support) provided by the sample for the null hypothesis.

Once we have the test statistic, we look into the z-table to calculate a value greater than or less than that. This will depend on whether it’s a two-tailed or a one-tailed test.

Lower-tailed Test

In a left-tailed hypothesis test, the decision rule will be as follows:

Assume that the level of significance is 10% (a = 0.10)

Under critical value approach, the decision rule will be as follows:

Reject the null hypothesis if test-statistic < -1.28

If the test statistic is -1.46, we will reject the null hypothesis.

We can calculate the p-value as follows:  We will look for the value of F(Z) where Z=-1.46. This gives us p-value = 0.072.

Under p-value approach, the decision rule will be as follows:

Since p-value (0.072) is less than a (0.10), we reject the null hypothesis. This is illustrated below:

Upper-tailed Test

In a right-tailed hypothesis test, the decision rule will be as follows:

Assume that the level of significance is 4% (a = 0.04)

Under critical value approach, the decision rule will be as follows:

Reject the null hypothesis if test-statistic > 1.75

1.75 is the value of z in z-table where F (Z) is (1 – 0.04) = 0.96

If the test statistic is 2.29, we will reject the null hypothesis.

We can calculate the p-value as follows:  We will look for the value of F(Z) where Z=2.29. This gives us p-value = 0.011. Note: At z=2.29, P(Z)=0.989. p-value = 1 – 0.989 = 0.011.

Under p-value approach, the decision rule will be as follows:

Since p-value (0.011) is less than a (0.04), we reject the null hypothesis. This is illustrated below:

Two-tailed Test

In a two-tailed hypothesis test, the decision rule will be as follows:

Assume that the level of significance is 3% (a = 0.03).

Under critical value approach, the decision rule will be as follows:

Reject the null hypothesis if test-statistic <= -2.17 or test-statistic >=2.17

2.17 is the value of z in z-table where F (Z) is (1 – 0.015) = 0.985

If the test statistic is -2.74 or 2.74, we will reject the null hypothesis.

We can calculate the p-value as follows:  We will look for the value of F(Z) where Z = 2.74. At z=2.74, P(Z)=0.9690. Probability of getting a value greater than 2.74 = 1-0.9690 = 0.0031. Since it’s a two tailed test, p-value = 2\*0.0031 = 0.0062.

Under p-value approach, the decision rule will be as follows:

Since p-value (0.0062) is less than a (0.03), we reject the null hypothesis. This is illustrated below:

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Decision Rule in Hypothesis Testing

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Selecting the Appropriate Test Statistic

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Hypothesis Testing

13 lessons

Lessons

1
What is Hypothesis Testing
2
Test Statistic, Type I and type II Errors, and Significance Level
3
Decision Rule in Hypothesis Testing
4
p-Value in Hypothesis Testing
5
Selecting the Appropriate Test Statistic
6
Hypothesis Testing with t-statistic
7
Hypothesis Testing with z-statistic
8
Tests Concerning Differences in Means
9
Paired Comparision Tests - Mean Differences When Populations are Not Independent
10
Hypothesis Tests Concerning Variances
11
Chi-square Test – Test for value of a single population variance
12
F-test - Test for the Differences Between Two Population Variances
13
Non-parametric Tests

Quizzes

Hypothesis Testing
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