A consumer products testing group is evaluating two competing brands of tires, Brand 1 and Brand 2. Though the two brands have been comparable in the past, some technological advances were recently made in the Brand 2 manufacturing process, and the consumer group is testing to see if Brand 2 will outperform Brand 1. Tread wear can vary considerably depending on the type of car, and the group is trying to eliminate this effect by installing the two brands on the same 12 cars, chosen at random. In particular, each car has one tire of each brand on its front wheels, with half of the cars chosen at random to have Brand 1 on the left front wheel, and the rest to have Brand 2 there. After all of the cars are driven over the standard test course for 20,000 miles, the amount of tread wear (in inches) is recorded, as shown in the table below. Car Brand 1 Brand 2 Difference (Brand 1- Brand 2) Send data to calculator 1 2 3 0.50 0.59 0.38 0.32 0.40 0.33 4 5 0.34 0.61 0.22 6 7 0.18 0.19 0.05 0.12 0.00 0.16 8 9 0.58 0.53 0.37 0.50 0.08 16 10 0.32 11 0.40 12 0.61 0.42 0.45 0.22 0.53 0.45 0.22 0.53 0.43 0.15-0.03 -0.13 0.18 -0.10 Based on these data, can the consumer group conclude, at the 0.01 level of significance, that the mean tread wear of Brand 1 exceeds that of Brand 2? Answer this question by performing a hypothesis test regarding μ (which is u with a letter "d" subscript), the population mean difference in tread wear for the two brands of tires. Assume that this population of differences (Brand 1 minus Brand 2) is normally distributed. Perform a one-tailed test. Then complete the parts below. Carry your intermediate computations to three or more decimal places and round your answers as specified. (If necessary, consult a list of formulas.)
A consumer products testing group is evaluating two competing brands of tires, Brand 1 and Brand 2. Though the two brands have been comparable in the past, some technological advances were recently made in the Brand 2 manufacturing process, and the consumer group is testing to see if Brand 2 will outperform Brand 1. Tread wear can vary considerably depending on the type of car, and the group is trying to eliminate this effect by installing the two brands on the same 12 cars, chosen at random. In particular, each car has one tire of each brand on its front wheels, with half of the cars chosen at random to have Brand 1 on the left front wheel, and the rest to have Brand 2 there. After all of the cars are driven over the standard test course for 20,000 miles, the amount of tread wear (in inches) is recorded, as shown in the table below. Car Brand 1 Brand 2 Difference (Brand 1- Brand 2) Send data to calculator 1 2 3 0.50 0.59 0.38 0.32 0.40 0.33 4 5 0.34 0.61 0.22 6 7 0.18 0.19 0.05 0.12 0.00 0.16 8 9 0.58 0.53 0.37 0.50 0.08 16 10 0.32 11 0.40 12 0.61 0.42 0.45 0.22 0.53 0.45 0.22 0.53 0.43 0.15-0.03 -0.13 0.18 -0.10 Based on these data, can the consumer group conclude, at the 0.01 level of significance, that the mean tread wear of Brand 1 exceeds that of Brand 2? Answer this question by performing a hypothesis test regarding μ (which is u with a letter "d" subscript), the population mean difference in tread wear for the two brands of tires. Assume that this population of differences (Brand 1 minus Brand 2) is normally distributed. Perform a one-tailed test. Then complete the parts below. Carry your intermediate computations to three or more decimal places and round your answers as specified. (If necessary, consult a list of formulas.)
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
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