## MATH 399N Week 6 Lab Assignment (2 Versions)

**Statistical Concepts:**

**Data Simulation****Confidence Intervals****Normal Probabilities**

##### Short Answer Writing Assignment

All answers should be complete sentences.

We need to find the confidence interval for the SLEEP variable. To do this, we need to find the mean and then find the maximum error. Then we can use a calculator to find the interval, (x – E, x + E)……..

- Give and interpret the 95% confidence interval for the hours of sleep a student gets. (5 points)
- Give and interpret the 99% confidence interval for the hours of sleep a student gets. (5 points)
- Compare the 95% and 99% confidence intervals for the hours of sleep a student gets. Explain the difference between these intervals and why this difference occurs. (10 points)
- Find the mean and standard deviation of the DRIVE variable by using
**=AVERAGE(A2:A36)**and**=STDEV(A2:A36)**. Assuming that this variable is normally distributed, what percentage of data would you predict would be less than 40 miles? This would be based on the calculated probability. Use the formula**=NORM.DIST(40, mean, stdev,TRUE)**. Now determine the percentage of data points in the dataset that fall within this range. To find the actual percentage in the dataset, sort the DRIVE variable and count how many of the data points are less than 40 out of the total 35 data points. That is the actual percentage. How does this compare with your prediction? (15 points) - What percentage of data would you predict would be between 40 and 70 and what percentage would you predict would be more than 70 miles? Subtract the probabilities found through
**=NORM.DIST(70, mean, stdev, TRUE)**and**=NORM.DIST(40, mean, stdev, TRUE)**for the “between” probability. To get the probability of over 70, use the same**=NORM.DIST(70, mean, stdev, TRUE)**and then subtract the result from 1 to get “more than”. Now determine the percentage of data points in the dataset that fall within this range, using same strategy as above for counting data points in the data set. How do each of these compare with your prediction and why is there a difference? (15 points)

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