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Martin Motors has in stock three cars of the same make and model. The Sales Mana

ID: 3150647 • Letter: M

Question

Martin Motors has in stock three cars of the same make and model. The Sales Manager would like to compare the gas consumption of the three cars (labeled car A, car B, and car C) using four different types of gasoline. For each trial, a gallon of gasoline was added to an empty tank, and the car was driven until it ran out of gas. The following table shows the number of miles driven in each trial.


Martin Motors has in stock three cars of the same make and model. The Sales Manager would like to compare the gas consumption of the three cars (labeled car A, car B, and car C) using four different types of gasoline. For each trial, a gallon of gasoline was added to an empty tank, and the car was driven until it ran out of gas. The following table shows the number of miles driven in each trial.

Explanation / Answer

Martin Motors has in stock three cars of the same make and model. The Sales Manager would like to compare the gas consumption of the three cars (labeled car A, car B, and car C) using four different types of gasoline. For each trial, a gallon of gasoline was added to an empty tank, and the car was driven until it ran out of gas. The following table shows the number of miles driven in each trial.

Distances in miles

Types of Gasoline

Car A

Car B

Car C

Regular

28.1

24

29.2

Super regular

24.1

22.5

26.4

Unleaded

23.5

26.5

23

Premium unleaded

25

24.5

26.3

Here, we have to use the chi square test for the independence between the distances in miles and the types of Gasoline. The null and alternative hypothesis for this test is given as below:

Null hypothesis: H0: The two categorical variables distances in miles and types of gasoline are independent.

Alternative hypothesis: H0: The two categorical variables distances in miles and types of gasoline is not independent.

The test statistic formula is given as below:

Chi-square = [(O – E) ^2 / E]

The chi square test for independence is given as below:

Chi-Square Test

Observed Frequencies

Distances in miles

Types of Gasoline

Car A

Car B

Car C

Total

Regular

28.1

24

29.2

81.3

Super regular

24.1

22.5

26.4

73

Unleaded

23.5

26.5

23

73

Premium unleaded

25

24.5

26.3

75.8

Total

100.7

97.5

104.9

303.1

Expected Frequencies

Distances in miles

Types of Gasoline

Car A

Car B

Car C

Total

Regular

27.01059

26.15226

28.13715

81.3

Super regular

24.25305

23.48235

25.2646

73

Unleaded

24.25305

23.48235

25.2646

73

Premium unleaded

25.18331

24.38304

26.23365

75.8

Total

100.7

97.5

104.9

303.1

Data

Level of Significance

0.05

Number of Rows

4

Number of Columns

3

Degrees of Freedom

6

Results

Critical Value

12.59159

Chi-Square Test Statistic

0.970521

p-Value

0.986705

Do not reject the null hypothesis

Expected frequency assumption

       is met.

Here, we get the p-value as 0.9867 which is greater than the given level of significance or alpha value 0.05, so we do not reject the null hypothesis that the two categorical variables distances in miles and types of gasoline are independent.

Distances in miles

Types of Gasoline

Car A

Car B

Car C

Regular

28.1

24

29.2

Super regular

24.1

22.5

26.4

Unleaded

23.5

26.5

23

Premium unleaded

25

24.5

26.3

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