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Chamberlain College of Nursing Week 7 Confidence Intervals Lab Questions

Chamberlain College of Nursing Week 7 Confidence Intervals Lab Questions

Chamberlain College of Nursing Week 7 Confidence Intervals Lab Questions

Steps to Complete the Week 7 Lab

Step 1: Find these articles in the _____ Library. Once you click each link, you will be logged into the Library and then click on “PDF Full Text”.

Step 2: Consider the use of confidence intervals in health sciences with these articles as inspiration and insights.

Step 3: Using the data you collected for the Week 5 Lab (heights of 10 different people that you work with), discuss your method of collection for the values that you are using in your study. What are some faults with this type of data collection? What other type of data collection could you have used, and how might this have affected your study?

Step 4: Now use the Week 6 Spreadsheet (Links to an external site.) to help you with calculations for the following questions/statements.

  1. Give a point estimate for the average height of all people at the place where you work. Start by putting the ten heights you are working with into the blue Data column of the spreadsheet. What is your point estimate, and what does this mean?

    example of adding a point estimate to spreadsheet

  2. Find a 95% confidence interval for the true mean height of all the people at your place of work. What is the interval?

    example of finding 95 percent confidence interval in spreadsheet

  3. Give a practical interpretation of the interval you found in part b, and explain carefully what the output means. (For example, you might say, “I am 95% confident that the true mean height of all of the people in my company is between 64 inches and 68 inches”).
  4. Post a screenshot of your work from the t value Confidence Interval for µ from the Confidence Interval tab on the Week 6 Excel spreadsheet

Step 5: Now, find a 99% confidence interval for the same data. Would the margin of error be larger or smaller for the 99% CI? Explain your reasoning.

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