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olga nikolaevna [1]
4 years ago
15

What is the purpose of calculating a confidence interval? Multiple Choice To provide a range of values that has a certain large

probability of containing the sample statistic of interest. To provide a range of values that, with a certain measure of confidence, contains the sample statistic of interest. To provide a range of values that, with a certain measure of confidence, contains the population parameter of interest. To provide a range of values that has a certain large probability of containing the population parameter of interest.
Mathematics
1 answer:
Nadusha1986 [10]4 years ago
8 0

Answer:

To provide a range of values that, with a certain measure of confidence, contains the population parameter of interest.  

To provide a range of values that has a certain large probability of containing the population parameter of interest.

Step-by-step explanation:

For estimating a parameter value, it is important to know the statement or degree of confidence that the interval contains the parameter value along with knowing the point estimate and the amount of possible error in the point estimate (which is the interval likely to contain the parameter value).Thus , an interval estimate of a population parameter is the confidence interval with a statement of confidence that the interval contains the parameter value. The confidence interval is a range of values around the statistic that are believed to contain, with a certain probability (say 99%) the true value of that statistic or the population value.

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Determine the sample size required to estimate the mean score on a standardized test within 5 points of the true mean with 99% c
Elodia [21]
Given:
Accuracy = 5
99% confidence interval
s = 17, sample standard deviation.

Because the population standard deviation is unknown, we should use the Student's t distribution.
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t*( \frac{s}{ \sqrt{n} )}
where
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That is,
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A table of t* values versus df (degrees of freedom) is as follows.
Note that df = n-1.

     n      df         t*
------ --------  -------
1001 1000  2.581
  101    100  2.626
   81      80  2.639
   61      60  2.660

We should evaluate iteratively until the guessed value, n, agrees with the computed value, N.

Try n = 1001 => df = 1000.
t* = 2.581
N = 11.56*(2.581²) = 77
No agreement.

Try n = 81 => df = 80
t* = 2.639
N = 11.56*(2.639²) = 80.5
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We conclude that n = 81.

Answer: The sample size is 81.

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