Sampling Methods A student obtains a sample of responses to the question “Do you plan to take or have you taken a statistics course?” A second student obtains a sample of responses to the same question. The first student surveys only males at the same college, and the second student surveys only females at the same college. What is wrong with the samples? Can randomization be used to overcome the flaws of those samples?
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 26m
- 11. Correlation1h 6m
- 12. Regression1h 35m
- 13. Chi-Square Tests & Goodness of Fit1h 57m
- 14. ANOVA1h 0m
9. Hypothesis Testing for One Sample
Steps in Hypothesis Testing
Problem 8.3.7
Textbook Question
Finding P-values
In Exercises 5–8, either use technology to find the P-value or use Table A-3 to find a range of values for the P-value. Based on the result, what is the final conclusion?
Cotinine in Smokers The claim is that smokers have a mean cotinine level greater than the level of 2.84 ng/mL found for nonsmokers. (Cotinine is used as a biomarker for exposure to nicotine.) The sample size is n = 902 and the test statistic is t = 56.319.

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Step 1: Understand the problem. The claim is that smokers have a mean cotinine level greater than 2.84 ng/mL. This is a one-tailed hypothesis test since the claim specifies 'greater than.' The test statistic provided is t = 56.319, and the sample size is n = 902.
Step 2: Identify the degrees of freedom (df). For a t-test, the degrees of freedom are calculated as df = n - 1, where n is the sample size. Substitute n = 902 into the formula to find df.
Step 3: Use the test statistic (t = 56.319) and degrees of freedom (df) to find the P-value. You can either use statistical software or a t-distribution table (Table A-3). If using the table, locate the range of P-values corresponding to the given t-value and df.
Step 4: Interpret the P-value. If the P-value is less than the significance level (commonly α = 0.05), reject the null hypothesis. Otherwise, fail to reject the null hypothesis. The null hypothesis states that the mean cotinine level for smokers is less than or equal to 2.84 ng/mL.
Step 5: Draw the final conclusion. Based on the P-value and the significance level, determine whether there is sufficient evidence to support the claim that smokers have a mean cotinine level greater than 2.84 ng/mL.

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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
P-value
The P-value is a statistical measure that helps determine the significance of results from a hypothesis test. It represents the probability of obtaining test results at least as extreme as the observed results, assuming that the null hypothesis is true. A smaller P-value indicates stronger evidence against the null hypothesis, often leading researchers to reject it in favor of the alternative hypothesis.
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Step 3: Get P-Value
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 data to determine whether to reject H0. The process includes calculating a test statistic, finding the P-value, and comparing it to a predetermined significance level (alpha) to draw conclusions.
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Step 1: Write Hypotheses
Test Statistic
A test statistic is a standardized value that is calculated from sample data during a hypothesis test. It measures how far the sample statistic is from the null hypothesis value, expressed in terms of standard errors. In this case, the test statistic is t = 56.319, which indicates a significant difference from the hypothesized mean cotinine level for nonsmokers, suggesting that smokers likely have a higher mean cotinine level.
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Step 2: Calculate Test Statistic
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