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Ch. 9 - Inferences from Two Samples
Triola - Elementary Statistics 14th Edition
Triola14th EditionElementary StatisticsISBN: 9780137366446당신이 사용하는 게 아니라요?교과서 변경
모든 교과서Triola 14th EditionCh. 9 - Inferences from Two Samples문제 6.R.6b
9장, 문제 6.R.6b

Smoking Cessation Programs


b. Does the difference between the success rate of the sustained care program and the standard care program appear to have practical significance?

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1
Identify the success rates for both the sustained care program and the standard care program. Denote these as p1 (sustained care) and p2 (standard care).
Calculate the difference in success rates: Δp = p1 - p2. This will give the observed difference in proportions.
Assess whether the observed difference Δp is large enough to be considered practically significant. Practical significance depends on the context and whether the difference is meaningful in real-world terms (e.g., does it justify additional costs or resources?).
Consider the sample sizes and variability in the data. Larger sample sizes reduce variability and make smaller differences more reliable, which can influence practical significance.
If needed, consult a predefined threshold for practical significance (e.g., a minimum difference that stakeholders consider meaningful) to determine if the observed difference meets this criterion.

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주요 개념

질문에 올바르게 답하기 위해 반드시 이해해야 하는 핵심 개념들은 다음과 같습니다.

Practical Significance

Practical significance refers to the real-world relevance or importance of a statistical finding. While a result may be statistically significant, indicating that it is unlikely to have occurred by chance, practical significance assesses whether the effect size is large enough to be meaningful in a practical context. In the case of smoking cessation programs, this would involve evaluating whether the difference in success rates translates into a noticeable improvement in outcomes for participants.
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가이드 코스
04:46
Step 4: State Conclusion Example 4

Effect Size

Effect size is a quantitative measure that reflects the magnitude of a phenomenon or the strength of a relationship between variables. In the context of comparing success rates of smoking cessation programs, effect size helps to determine how substantial the difference is between the sustained care and standard care programs. A larger effect size indicates a more significant difference, which can inform decisions about which program to implement.
추천 영상:
04:08
Finding the Minimum Sample Size Needed for a Confidence Interval

Statistical Significance

Statistical significance assesses whether the observed differences in data are likely due to chance or represent a true effect. It is typically determined using a p-value, where a p-value less than a predetermined threshold (commonly 0.05) suggests that the results are statistically significant. Understanding statistical significance is crucial when evaluating the success rates of different smoking cessation programs, as it helps to validate the findings before considering their practical implications.
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가이드 코스
05:53
Parameters vs. Statistics
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교과서 질문

Finding Critical Values

In Exercises 17–20, refer to the information in the given exercise and use a 0.05 significance level for the following.


a. Find the critical value(s).

b. Should we reject H0 or should we fail to reject H0?


Exercise 14

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교과서 질문

Color and Recall Researchers from the University of British Columbia conducted trials to investigate the effects of color on the accuracy of recall. Subjects were given tasks consisting of words displayed on a computer screen with background colors of red and blue. The subjects studied 36 words for 2 minutes, and then they were asked to recall as many of the words as they could after waiting 20 minutes. Results from scores on the word recall test are given below. Use a 0.05 significance level to test the claim that variation of scores is the same with the red background and blue background.


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교과서 질문

Randomization with Commute Times Given the two samples of commute times (minutes) shown here, which of the following are randomizations of them?


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a. Boston: 10 10 60. New York: 5 20 25 30 45.

b. Boston: 10 10 60 20 25. New York: 5 30 45.

c. Boston: 5 10 25 25 60. New York: 5 30 30 60.

d. Boston: 10 10 60. New York: 5 20 25 30 45.

e. Boston: 10 10 10 10 10. New York: 60 60 60.

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교과서 질문

In Exercises 17–24, use the indicated Data Sets from Appendix B. The complete data sets can be found at www.TriolaStats.com. Assume that the paired sample data are simple random samples and the differences have a distribution that is approximately normal.

Measured and Reported Weights Repeat Example 1 using all of the 2784 measured and reported weights of males listed in Data Set 4 “Measured and Reported” in Appendix B. Did the larger data set have much of an effect on the results?

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