Reference no: EM131245513
You will learn about how to use a sample statistic (such as a sample mean) to estimate the value of a population parameter (such as the true population mean). For example, you can estimate the true mean weight of all newborn babies in the entire world by collecting a sample. Because the sample is only a small portion of the entire population, errors will have to be considered. Using a sample to create a range or interval of values that estimates a population value is called a "confidence interval."
The formula for calculating a 95% confidence interval for a population mean is:
Confidence Interval for Population Mean:
sample mean - E < population mean < sample mean + E
Error "E" = (1.96)*(s) / sqrt(n)
"s" is the standard deviation and "n" is the sample size.
Part 1: Confidence Intervals
Why is it often impossible to know the actual value of any population parameter? Give an example of a population parameter that you cannot calculate, but that you can estimate.
A sample can be used to estimate a population parameter. How does the sample size affect the estimate? If the sample is larger, what will this do to the error E?
Use the Confidence Interval formula above and calculate the 95% confidence interval for any population mean of your choice. Write down (invent) the sample size (be sure it is 30 or above), the sample mean, and the sample standard deviation. Then, calculate the confidence interval. Remember, you are inventing all the values, so no two posts should look the same.
Use Excel and your invented values to calculate the confidence interval. Include and compare the results. (Tutorials can be found in Doc Sharing). Again, remember that your sample size must be 30 or above.
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