jernplate8
2021-02-16
Answered

Participants enter a research study with unique characteristics that produce different scores from one person to another. For an independent-measures study, these individual differences can cause problems. Identify the problems and briefly explain how they are eliminated or reduced with a repeated-measures study. Independent-measures study is used in the study.

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Delorenzoz

Answered 2021-02-17
Author has **91** answers

Justification:

Since, participants produce different scores from one person to another and the independent-measures study is used. The first problem is the large differences in scores of participants because of grouping. Since, groups are independent so, there are chances that 2 groups are formed in such a way that they differ a lot in some characteristics. So, there can be large differences in participants score by grouping only.

Second problem can be the large variance, since, there exist individual differences of score due to which overall variance increases.

Both the problems can be eliminated by using repeated-measures study design because in this study participants in both the groups are same, therefore there will not be grouping error. Also, in repeated-measures study design, individual variance vanishes.

Conclusion:

The problems in independent measures design are grouping error and larger variance because of individual variances. The problems can be eliminated by using repeated-measures design.

Since, participants produce different scores from one person to another and the independent-measures study is used. The first problem is the large differences in scores of participants because of grouping. Since, groups are independent so, there are chances that 2 groups are formed in such a way that they differ a lot in some characteristics. So, there can be large differences in participants score by grouping only.

Second problem can be the large variance, since, there exist individual differences of score due to which overall variance increases.

Both the problems can be eliminated by using repeated-measures study design because in this study participants in both the groups are same, therefore there will not be grouping error. Also, in repeated-measures study design, individual variance vanishes.

Conclusion:

The problems in independent measures design are grouping error and larger variance because of individual variances. The problems can be eliminated by using repeated-measures design.

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The centers for Disease Control reported the percentage of people 18 years of age and older who smoke (CDC website, December 14, 2014). Suppose that a study designed to collect new data on smokers and Questions Navigation Menu preliminary estimate of the proportion who smoke of .26.

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a) How large a sample should be taken to estimate the proportion of smokers in the population with a margin of error of .02?(to the nearest whole number) Use 95% confidence.

b) Assume that the study uses your sample size recommendation in part (a) and finds 520 smokers. What is the point estimate of the proportion of smokers in the population (to 4 decimals)?

c) What is the 95% confidence interval for the proportion of smokers in the population?(to 4 decimals)?

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43 58 61 67 74

a. What quarter has the smallest spread of data?

- Third

- First

- Fourth

- Second

b. What is that spread?

c. What quarter has the largest spread of data?

- Fourth

- Second

- First

- Third

43 58 61 67 74

a. What quarter has the smallest spread of data?

- Third

- First

- Fourth

- Second

b. What is that spread?

c. What quarter has the largest spread of data?

- Fourth

- Second

- First

- Third

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