The means of the number of revolutions per minute of two competing engines are to be compared. Thirty engines of each type are randomly selected and tested. Both populations are assumed to have normal distributions. The table below shows the result. Do the data indicate that Engine 2 has different RPM than Engine 1? Justify by using a confidence interval or a hypothesis test with α = 0.05. Justify fully. What type of error are you in danger of making? Engine Sample Mean Standard Deviation 1 1625 50 2 1650 60

The means of the number of revolutions per minute of two competing engines are to be compared. Thirty engines of each type are randomly selected and tested. Both populations are assumed to have normal distributions. The table below shows the result. Do the data indicate that Engine 2 has different RPM than Engine 1? Justify by using a confidence interval or a hypothesis test with α = 0.05. Justify fully. What type of error are you in danger of making? Engine Sample Mean Standard Deviation 1 1625 50 2 1650 60

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter10: Statistics

Section10.5: Comparing Sets Of Data

Problem 14PPS

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Question

The means of the number of revolutions per minute of two competing engines are to be compared. Thirty engines of each type are randomly selected and tested. Both populations are assumed to have normal distributions. The table below shows the result. Do the data indicate that Engine 2 has different RPM than Engine 1? Justify by using a confidence interval or a hypothesis test with α = 0.05. Justify fully. What type of error are you in danger of making?

Engine	Sample Mean	Standard Deviation
1	1625	50
2	1650	60

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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