Dive Duration An oceanographer claims that the mean dive duration of a North Atlantic right whale is 11.5 minutes. A random sample of 34 dive durations has a mean of 12.2 minutes and a standard deviation of 2.2 minutes. Is there enough evidence to reject the claim at α=0.10?
Table of contents
- 1. Intro to Stats and Collecting Data55m
- 2. Describing Data with Tables and Graphs1h 55m
- 3. Describing Data Numerically1h 45m
- 4. Probability2h 16m
- 5. Binomial Distribution & Discrete Random Variables2h 33m
- 6. Normal Distribution and Continuous Random Variables1h 38m
- 7. Sampling Distributions & Confidence Intervals: Mean1h 53m
- 8. Sampling Distributions & Confidence Intervals: Proportion1h 12m
- 9. Hypothesis Testing for One Sample2h 19m
- 10. Hypothesis Testing for Two Samples3h 22m
- 11. Correlation1h 6m
- 12. Regression1h 4m
- 13. Chi-Square Tests & Goodness of Fit1h 20m
- 14. ANOVA1h 0m
9. Hypothesis Testing for One Sample
Performing Hypothesis Tests: Means
Problem 7.Q.1
Textbook Question
A hat company claims that the mean hat size for a male is at least 7.25. A random sample of 12 hat sizes has a mean of 7.15. At α=0.01, can you reject the company’s claim? Assume the population is normally distributed and the population standard deviation is 0.27.

1
Step 1: Define the null hypothesis (H₀) and the alternative hypothesis (Hₐ). The null hypothesis is H₀: μ ≥ 7.25 (the mean hat size is at least 7.25). The alternative hypothesis is Hₐ: μ < 7.25 (the mean hat size is less than 7.25). This is a one-tailed test.
Step 2: Identify the test statistic to use. Since the population standard deviation (σ) is known and the sample size is small (n = 12), use the z-test formula: z = (x̄ - μ₀) / (σ / √n), where x̄ is the sample mean, μ₀ is the hypothesized population mean, σ is the population standard deviation, and n is the sample size.
Step 3: Calculate the critical value for the z-test at α = 0.01 for a one-tailed test. Use a z-table or statistical software to find the z-critical value corresponding to a left-tailed test with α = 0.01.
Step 4: Compute the test statistic using the formula from Step 2. Substitute the given values: x̄ = 7.15, μ₀ = 7.25, σ = 0.27, and n = 12. Simplify the expression to find the z-value.
Step 5: Compare the calculated z-value to the critical z-value. If the calculated z-value is less than the critical z-value, reject the null hypothesis (H₀). Otherwise, fail to reject the null hypothesis. Interpret the result in the context of the problem to determine if the company's claim can be rejected.

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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
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). In this case, the null hypothesis states that the mean hat size is at least 7.25, while the alternative suggests it is less than 7.25. The goal is to determine whether the sample data provides sufficient evidence to reject the null hypothesis.
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Step 1: Write Hypotheses
Significance Level (α)
The significance level, denoted as α, is the threshold for determining whether to reject the null hypothesis. In this scenario, α is set at 0.01, meaning there is a 1% risk of concluding that the mean hat size is less than 7.25 when it is actually true. A lower α indicates a stricter criterion for rejecting the null hypothesis, which helps control the probability of making a Type I error.
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Z-Test for Means
A Z-test for means is used when the population standard deviation is known and the sample size is small (n < 30). It compares the sample mean to the population mean under the null hypothesis. In this case, the Z-test will help determine if the sample mean of 7.15 is significantly lower than the claimed mean of 7.25, using the provided population standard deviation of 0.27 to calculate the Z-score.
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