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Thensive Quiz
In a sample of 10 randomly selected women, it was found that their mean height was 63.4 inches. From previous studies, it can be assumed that the population standard
deviation is 2.4 and that the population of height measurements is normally distributed. Construct the confidence interval for the population mean. 12 possible
A.
B.
C.
D.

Ask by Lang Estrada. in the United States
Dec 13,2024

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The confidence interval for the population mean is approximately .

Solución

To construct a confidence interval for the population mean, we can use the formula for the confidence interval when the population standard deviation is known:
Where:
  • is the sample mean
  • is the z-score corresponding to the desired confidence level
  • is the population standard deviation
  • is the sample size
Given:
  • Sample mean inches
  • Population standard deviation
  • Sample size
  1. Find the z-score for a confidence level:
    The z-score for a confidence level is approximately .
  2. Calculate the standard error (SE):
  3. Calculate the margin of error (ME):
  4. Construct the confidence interval:
Thus, the confidence interval for the population mean is approximately .
The correct answer is:
A. .

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Beyond the Answer

To construct a confidence interval for the population mean, we can use the formula for the confidence interval:
Where:
  • (sample mean)
  • (population standard deviation)
  • (sample size)
  • is the z-value corresponding to the desired confidence level (approximately 1.96 for confidence)
Calculating the standard error (SE):
Now, using the z-score to calculate the margin of error:
Now, calculate the confidence interval:
Rounding to one decimal place, the confidence interval is approximately .
So the answer is A. .

Confidence intervals give you a range of plausible values for the population mean based on your sample data. It’s like having a safety net—if you were to repeat the process many times, you expect the true mean to fall within this range in of the cases!
Understanding how these intervals work in practice can be crucial, especially in fields like medicine or economics, where decisions depend on estimating values based on sample data. They’re not just numbers; they represent the uncertainty and reliability of our estimates!

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