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photoshop1234 [79]
3 years ago
9

A 99% confidence interval estimate can be interpreted to mean that A. if all possible samples are taken and confidence interval

estimates are developed, 99% of them would include the true population mean somewhere within their interval. B. we have 99% confidence that we have selected a sample whose interval does include the population mean. C. Both of the above. D. None of the above..
Social Studies
1 answer:
Alex Ar [27]3 years ago
5 0

Answer:

Option (C) is correct.

Explanation:

Confidence interval is a type of range which includes the true value of the population parameter. Confidence interval can be determined from the statistics of the researched data.

For example:

z_c = 1.96 at 95% confidence ⇒ Z- critical value

n = 50

x - bar = 375  

SD = 20

Margin of error, E = ?

E = 5.5437

Therefore,

95% CI:

= (375 - 5.5437, 375 + 5.5437)

= (369.4563 , 380.5437)

Hence, 95% confidence interval is (369.4563, 380.5437). This includes the value of x-bar = 375 in the confidence interval.

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Hello. This question is incomplete. The full question is:

"Dr. Parrett is a sports psychologist for a large Southern university. The provost and chancellor have asked him to examine the relationship between athletic performance and academic stress at the university. For example, is it the case that the most talented athletes experience the greatest concern over their grades? The provost and chancellor have made it clear to Dr. Parrett that they want a large amount of external validity in the study. He has valid and reliable measures of both athletic performance and academic stress. He knows that he does not have the time or the money to study the entire population of interest.

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The four types of nonprobability sampling are convenience sampling, purposive sampling, quota sampling, and snowball sampling.

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Convenience sampling: Allows a selection to be made of a small sample of the target population of the research. This sample is made up of individuals who are available and accessible to research and not through statistical criteria. Regarding the question above, Dr. Parrett can select the athletes he knows and who would like to participate in the research.

Purposive sampling: It allows the sample to be controlled whenever a certain manipulation is possible to generate expected and known results. In the case of the question above, Dr Parrett can search for specific athletes, with characteristics that will generate an expected result in the research.

Snowball sampling: Allows the individuals who make up the sample to invite other individuals to compose the sample, who in turn can invite other individuals. In the case of the question above, Dr. Parret can invite the athletes he wants and ask them to call friends to participate in the survey as well.

Sampling quota: Allows the individuals who will compose the sample to be selected due to their characteristics and qualities. Regarding the question above, Dr. Parrett could only summon athletes with high marks.

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