Help finding: Test the null hypothesis that the mean head injury for each vehicle type is the same at theα=0.01level of significance.What is the F0What is the P ValueDraw a box plot A highway safety institution conducts experiments in which cars are crashed into a fixed barrier at 40 mph. In the institute's 40-mph offset test, 40% of the total width of each vehicle strikes a barrier on the driver's side. Thebarrier's deformable face is made of aluminum honeycomb, which makes the forces in the test similar to those involved in a frontal offset crash between two vehicles of the same weight, each going just less than 40 mph. Youare in the market to buy a family car and you want to know if the mean head injury resulting from this offset crash is the same for large family cars, passenger vans, and midsize utility vehicles (SUVS). The data in theaccompanying table were collected from the institute's study. Complete parts (a) through (d) below.Click the icon to view the data table.Head injuries.....(a) State the null and alternative hypotheses.A. Ho: HCars = HVans = HsUVs and H,: at least one mean is differentLarge Family Cars Passenger Vans Midsize Utility Vehicles (SUVS)B. Ho: HCars = HVans = HsUVs and H,: all means are different261148224134240215O C. Ho: HCars = Hvans = Hsuvs and H,: HCars < HVans

Answered: Help finding: Test the null…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Help finding:

Test the null hypothesis that the mean head injury for each vehicle type is the same at the
α=0.01
level of significance.
1. 1. What is the F0
  2. What is the P Value
Draw a box plot

A highway safety institution conducts experiments in which cars are crashed into a fixed barrier at 40 mph. In the institute's 40-mph offset test, 40% of the total width of each vehicle strikes a barrier on the driver's side. The
barrier's deformable face is made of aluminum honeycomb, which makes the forces in the test similar to those involved in a frontal offset crash between two vehicles of the same weight, each going just less than 40 mph. You
are in the market to buy a family car and you want to know if the mean head injury resulting from this offset crash is the same for large family cars, passenger vans, and midsize utility vehicles (SUVS). The data in the
accompanying table were collected from the institute's study. Complete parts (a) through (d) below.
Click the icon to view the data table.
Head injuries
.....
(a) State the null and alternative hypotheses.
A. Ho: HCars = HVans = HsUVs and H,: at least one mean is different
Large Family Cars Passenger Vans Midsize Utility Vehicles (SUVS)
B. Ho: HCars = HVans = HsUVs and H,: all means are different
261
148
224
134
240
215
O C. Ho: HCars = Hvans = Hsuvs and H,: HCars < HVans <Hsuvs
411
343
184
525
695
307
(b) Normal probability plots indicate that the sample data come from normal populations. Are the requirements to use the one
148
546
355
A. No, because the populations are not normally distributed.
632
468
554
166
321
399
B. No, because the largest sample standard deviation is more than twice the smallest sample standard deviation.
C. Yes, all the requirements for use of a one-way ANOVA procedure are satisfied.
D. No, because the samples are not independent.
Print
Done
(c) Test the hypothesis that the mean head injury for each vehicle type is the same at the a = 0.01 level of significance.
Use technology to find the F-test statistic for this data set.
Fo = |(Round to three decimal places as needed.)

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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