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Aviation Institute of Maintenance Dallas Statistics Questions

Aviation Institute of Maintenance Dallas Statistics Questions

Aviation Institute of Maintenance Dallas Statistics Questions

Question Description

I’m working on a statistics exercise and need an explanation and answer to help me learn.

1.Whileattempting to measure its risk exposure for the upcoming year, aninsurance company notices a trend between the age of a customer and thenumber of claims per year. It appears that the number of claims keepgoing up as customers age. After performing a regression, they find thatthe relationship is (number of claims per year) = 2.046*(age) + 4.976.Interpret the slope.

1)

When number of claims per year increases by 1 claim, age increases by 4.976 years.

2)

When number of claims per year increases by 1 claim, age increases by 2.046 years.

3)

When age increases by 1 year, number of claims per year increases by 2.046 claims per year.

4)

When age increases by 1 year, number of claims per year increases by 4.976 claims per year.

5)

We are not given the dataset, so we cannot make an interpretation.

2.Supposethat in a certain city, the rent of an apartment is proportional to thesize of the apartment in square feet. You use regression to try toquantify this relationship and the regression output from a sample of 10apartments is shown below. What can we conclude about the slope ofsize?

1)

Since we are not given the dataset, we do not have enough information to determine if the slope differs from 0.

2)

Not enough evidence was found to conclude the slope differs significantly from 0.

3)

The slope is 0.248 and therefore differs from 0.

4)

The slope is equal to 0.

5)

The slope significantly differs from 0.

3.Suppose that a researcher wants to predict the weight of female collegeathletes based on their height, percent body fat, and age. A sample istaken and the following regression table is produced. Based on theF-test alone, what is the correct conclusion about the regressionslopes?

1)

We do not have the dataset, therefore, we are unable to make a conclusion about the slopes.

2)

All the regression slopes do not equal zero.

3)

All the regression slopes are equal to zero.

4)

At least one of the regression slopes does not equal zero.

5)

We did not find significant evidence to conclude that at least one slop

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