Discarded Plastic Find the test statistic used for the hypothesis test described in Exercise 1.
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 9.3.7b
Textbook Question
In Exercises 5–16, use the listed paired sample data, and assume that the samples are simple random samples and that the differences have a distribution that is approximately normal.
The Freshman 15 The “Freshman 15” refers to the belief that college students gain 15 lb (or 6.8 kg) during their freshman year. Listed below are weights (kg) of randomly selected male college freshmen (from Data Set 13 “Freshman 15” in Appendix B). The weights were measured in September and later in April.
b. Construct the confidence interval that could be used for the hypothesis test described in part (a). What feature of the confidence interval leads to the same conclusion reached in part (a)?


1
Step 1: Calculate the differences between the paired weights for September and April. For each pair, subtract the September weight from the April weight to find the difference (April - September).
Step 2: Compute the mean of the differences. Add all the differences together and divide by the number of pairs to find the average difference.
Step 3: Calculate the standard deviation of the differences. Use the formula for standard deviation: \( s = \sqrt{\frac{\sum (x_i - \bar{x})^2}{n-1}} \), where \( x_i \) are the differences, \( \bar{x} \) is the mean of the differences, and \( n \) is the number of pairs.
Step 4: Determine the standard error of the mean difference using the formula \( SE = \frac{s}{\sqrt{n}} \), where \( s \) is the standard deviation of the differences and \( n \) is the number of pairs.
Step 5: Construct the confidence interval using the formula \( \bar{x} \pm t \cdot SE \), where \( \bar{x} \) is the mean difference, \( t \) is the critical t-value from the t-distribution table for the desired confidence level, and \( SE \) is the standard error. Interpret the confidence interval to determine whether it includes 0, which would lead to the same conclusion as the hypothesis test in part (a).

This video solution was recommended by our tutors as helpful for the problem above
Video duration:
8mPlay a video:
Was this helpful?
Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Paired Sample Data
Paired sample data involves two related groups where measurements are taken from the same subjects at different times or under different conditions. In this context, the weights of male college freshmen are measured in September and again in April, allowing for a direct comparison of weight changes over time.
Recommended video:
Sampling Distribution of Sample Proportion
Confidence Interval
A confidence interval is a range of values, derived from sample statistics, that is likely to contain the true population parameter with a specified level of confidence, typically 95%. In this case, constructing a confidence interval for the weight differences will help assess whether the average weight gain aligns with the hypothesis of the 'Freshman 15.'
Recommended video:
Introduction to Confidence Intervals
Hypothesis Testing
Hypothesis testing is a statistical method used to make inferences about population parameters based on sample data. In this scenario, the null hypothesis might state that there is no significant weight gain among freshmen, while the alternative hypothesis suggests that there is a significant gain. The results from the confidence interval can support or refute this hypothesis.
Recommended video:
Guided course
Step 1: Write Hypotheses
Watch next
Master Step 1: Write Hypotheses with a bite sized video explanation from Patrick
Start learningRelated Videos
Related Practice
Textbook Question
47
views