Skip to main content
Ch. 9 - Inferences from Two Samples
Triola - Elementary Statistics 14th Edition
Triola14th EditionElementary StatisticsISBN: 9780137366446당신이 사용하는 게 아니라요?교과서 변경
9장, 문제 3

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


[Image]


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.

검증된 단계별 안내
1
Step 1: Understand the concept of randomization. Randomization involves rearranging or redistributing the data points between groups while maintaining the total number of data points in each group. This process ensures that the groups are formed randomly without any inherent bias.
Step 2: Analyze the original samples provided. The original commute times are: Boston: 10, 10, 60 and New York: 5, 20, 25, 30, 45. These are the baseline distributions of commute times for the two cities.
Step 3: Evaluate each option to determine if it represents a valid randomization. For a valid randomization, the total number of data points in each group must remain consistent with the original sample sizes (Boston: 3 data points, New York: 5 data points), and the data points must be redistributed randomly between the groups.
Step 4: Check for duplicates or patterns that might indicate non-randomization. For example, in option (e), Boston has all identical values (10, 10, 10, 10, 10), and New York has all identical values (60, 60, 60). This is not a randomization but rather a systematic grouping.
Step 5: Compare each option to the original samples and verify whether the redistribution of data points adheres to the principles of randomization. Ensure that the total number of data points and the original values are preserved in the new groupings.

비슷한 문제에 대한 검증된 영상 답변:

이 영상 해법은 위 문제에 도움이 된다고 튜터들이 추천한 것입니다.
영상 길이:
1m
도움이 되었나요?

주요 개념

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

Randomization

Randomization is a statistical technique used to assign individuals or items to different groups in a way that eliminates bias. In the context of comparing two samples, randomization ensures that the samples are representative of the population, allowing for valid conclusions about differences or similarities. It is crucial for ensuring that the results of an analysis are not influenced by external factors.
추천 영상:
가이드 코스
07:09
Intro to Random Variables & Probability Distributions

Sample Size and Composition

Sample size refers to the number of observations or data points collected in a study. The composition of a sample, including its distribution and range of values, affects the reliability of statistical analyses. In the given question, understanding the sample sizes and their respective values is essential to determine if the proposed randomizations maintain the integrity of the original samples.
추천 영상:
05:11
Sampling Distribution of Sample Proportion

Statistical Validity

Statistical validity refers to the extent to which the conclusions drawn from a statistical analysis are accurate and applicable to the real world. This includes ensuring that the samples used are appropriate for the analysis being conducted. In the context of the question, assessing whether the proposed randomizations preserve the original sample characteristics is key to determining their validity.
추천 영상:
가이드 코스
05:53
Parameters vs. Statistics