The manufacturer of a gasoline additive claims that the use of this additive increases gasoline mileage. A random sample of 6 cars was selected, and these cars were driven for one week without the gasoline additive and then for one week with the additive. The following table gives the mileage (in miles per gallon) for these cars with and without the additive:Car 1 2 3 4 5 6Mileage Without Additive 24.6 28.3 18.9 23.7 15.4 29.5 Mileage With Additive 26.3 31.7 18.2 25.3 18.3 30.9Assuming mileages are normally distributed, can you conclude that the use of the gasoline additive increases mileage at the 2.5% significance level?

Solution: Given information: n= 6 Sample size Let x= Mileage Without Additive and y=Mileage With…

Answered: The manufacturer of a gasoline additive…

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)

6th Edition

ISBN:9781337111348

Author:Bruce Crauder, Benny Evans, Alan Noell

Publisher:Bruce Crauder, Benny Evans, Alan Noell

Chapter5: A Survey Of Other Common Functions

Section5.3: Modeling Data With Power Functions

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The manufacturer of a gasoline additive claims that the use of this additive increases gasoline mileage. A random sample of 6 cars was selected, and these cars were driven for one week without the gasoline additive and then for one week with the additive. The following table gives the mileage (in miles per gallon) for these cars with and without the additive:

Car 1 2 3 4 5 6

Mileage Without Additive 24.6 28.3 18.9 23.7 15.4 29.5

Mileage With Additive 26.3 31.7 18.2 25.3 18.3 30.9

Assuming mileages are normally distributed, can you conclude that the use of the gasoline additive increases mileage at the 2.5% significance level?

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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