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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: 9780137493470Non è quello che usi tu?Cambia libro di testo
Capitolo 7, Problema 7.3.15

In Exercises 13–18, test the claim about the population mean μ at the level of significance α. Assume the population is normally distributed.
Claim: μ≥8000; α=0.01. Sample statistics: x_bar=77,000, s=450, n=25

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Step 1: Identify the null hypothesis (H₀) and the alternative hypothesis (Hₐ). The claim is μ ≥ 8000, so the null hypothesis is H₀: μ ≥ 8000, and the alternative hypothesis is Hₐ: μ < 8000. This is a left-tailed test.
Step 2: Calculate the test statistic using the formula for a t-test: t = (x̄ - μ₀) / (s / √n), where x̄ is the sample mean, μ₀ is the hypothesized population mean, s is the sample standard deviation, and n is the sample size. Substitute the given values: x̄ = 77000, μ₀ = 8000, s = 450, and n = 25.
Step 3: Determine the critical value for the t-distribution at the significance level α = 0.01 with degrees of freedom (df) = n - 1 = 25 - 1 = 24. Use a t-table or statistical software to find the critical value for a left-tailed test.
Step 4: Compare the calculated test statistic to the critical value. If the test statistic is less than the critical value, reject the null hypothesis H₀. Otherwise, fail to reject H₀.
Step 5: State the conclusion in the context of the problem. Based on the comparison in Step 4, determine whether there is sufficient evidence to reject the claim that μ ≥ 8000 at the 0.01 significance level.

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Hypothesis Testing

Hypothesis testing is a statistical method used to make decisions about a population based on sample data. It involves formulating a null hypothesis (H0) and an alternative hypothesis (H1), then using sample statistics to determine whether to reject H0 in favor of H1. In this case, the null hypothesis would be that the population mean μ is less than 8000, while the alternative hypothesis would assert that μ is greater than or equal to 8000.
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Step 1: Write Hypotheses

Level of Significance (α)

The level of significance, denoted as α, is the threshold for determining whether to reject the null hypothesis. It represents the probability of making a Type I error, which occurs when the null hypothesis is incorrectly rejected. In this scenario, α is set at 0.01, indicating a 1% risk of concluding that the population mean is greater than or equal to 8000 when it is not.
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Step 4: State Conclusion Example 4

Sample Statistics

Sample statistics are numerical values calculated from a sample that provide insights into the population from which the sample is drawn. In this question, the sample mean (x̄ = 77,000), sample standard deviation (s = 450), and sample size (n = 25) are crucial for conducting the hypothesis test. These statistics will be used to calculate the test statistic and determine whether the evidence supports the claim about the population mean.
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Sampling Distribution of Sample Proportion
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