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Ch. 7 - Hypothesis Testing with One Sample
Larson - Elementary Statistics: Picturing the World 8th Edition
Larson8th EditionElementary Statistics: Picturing the WorldISBN: 9780137493470Not the one you use?Change textbook
Chapter 7, Problem 7.3.4

In Exercises 3–8, find the critical value(s) and rejection region(s) for the type of t-test with level of significance alpha and sample size n.


Left-tailed test, α=0.01, n=35

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Determine the degrees of freedom (df) for the t-test. The formula for degrees of freedom is df = n - 1, where n is the sample size. In this case, df = 35 - 1.
Identify the level of significance (α) for the test. Here, α = 0.01, which represents the probability of rejecting the null hypothesis when it is true.
Since this is a left-tailed test, locate the critical value of t corresponding to α = 0.01 and df = 34 using a t-distribution table or statistical software. The critical value will be negative because it is a left-tailed test.
Define the rejection region for the test. For a left-tailed test, the rejection region is t < critical value, where the critical value is the t-score found in the previous step.
Summarize the critical value and rejection region. Clearly state that if the test statistic falls within the rejection region, the null hypothesis will be rejected.

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Key Concepts

Here are the essential concepts you must grasp in order to answer the question correctly.

Critical Value

A critical value is a threshold that determines the boundary for rejecting the null hypothesis in hypothesis testing. It is derived from the chosen significance level (alpha) and the distribution of the test statistic. For a left-tailed t-test, the critical value is the point below which the null hypothesis is rejected, indicating that the sample provides sufficient evidence against it.
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Critical Values: t-Distribution

Rejection Region

The rejection region is the range of values for the test statistic that leads to the rejection of the null hypothesis. In a left-tailed test, this region is located to the left of the critical value. If the calculated test statistic falls within this region, it suggests that the observed data is unlikely under the null hypothesis, prompting researchers to consider alternative explanations.
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Step 4: State Conclusion

T-Test

A t-test is a statistical test used to compare the means of two groups or to compare a sample mean to a known value when the population standard deviation is unknown. It is particularly useful for small sample sizes (typically n < 30) and is based on the t-distribution. The type of t-test (one-sample, independent, or paired) depends on the data structure and research question.
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Related Practice
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Textbook Question

Finding a P-Value In Exercises 13–18, find the P-value for the hypothesis test with the standardized test statistic z. Decide whether to reject H0 for the level of significance alpha.

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z= 1.95

alpha=0.08