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miv72 [106K]
3 years ago
5

Information about the proportion of a sample that agrees with a certain statement is given below. Use StatKey or other technolog

y to estimate the standard error from a bootstrap distribution generated from the sample. Then use the standard error to give a confidence interval for the proportion of the population to agree with the statement. StatKey tip: Use "CI for Single Proportion" and then "Edit Data" to enter the sample information. Click here to access StatKey. In a random sample of 400 people, 112 agree and 288 disagree. Estimate the standard error using 1000 samples.

Mathematics
1 answer:
nydimaria [60]3 years ago
4 0

Answer:

Answer is given below.

Step-by-step explanation:

Number of people, n = 400

Number of people who agree with the statement is 112.

Number of people who disagree with the statement is 288

Using Stat Key, follow the steps below to obtain the 95% confidence interval for the

proportion of the population to agree with the statement.

1) Open  

2) Click on CI for single proportion.

3) Click Edit data key.

4) Enter 112 in count text box.

5) Enter 400 in Sample size text box.

6) Click two-tail.

7) Click Generate 1000 samples key.

Output:  (See Image).

Original Sample

Count   SampleSize    Proportion

112       400       0.280

Bootstrap Sample

Count SampleSize Proportion

128    400        0.320

From the above dot plot , it can be observed that the standard error shows top right corner.

Thus the standard error is 0.022.

From the output, the 95% confidence interval is 0.2371 to 0.325  

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Read the following excerpts from the New York Times (December 17, 1996) article Chance of Heart Attack Increases for Those Who S
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1. B

2. A

3. A

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Hello!

The study claimed that subjects who suffer depression are more likely to have a heart attack than those who are not depressed.

1551 persons were interviewed as part of the experiment and classified according to their answers in two groups "suffered depression" and "didn't suffer depression"

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1.

An observational study is one where the researcher only determines the variables he wants to study without controlling or influencing any factor of the population of interest. Because there is no interference from the researchers, there is a high risk that confounding factors may affect the conclusions of it. These studies are usually precursors to experimental tests, it allows the researcher to have an idea of the association between the two variables but you cannot establish causal relationships from them.

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Of the 1551 subjects originally studied, 444 were classified as depressed, of these 27 had heard attacks. You can calculate the "proportion of subjects that suffered depression and had heart attacks" as:

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