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Stats homework help

Question 1 of 17
1.0 Points

A researcher hypothesizes that the variation in the amount of money spent on business dinners is greater than the variation of the amount of money spent on lunches. The variance of nine business dinners was $6.12 and the variance of 12 business lunches was $0.87. What is the test value?

 
 
 
 

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Question 2 of 17
1.0 Points
An investor wants to compare the risks associated with two different stocks. One way to measure the risk of a given stock is to measure the variation in the stock’s daily price changes. 

In an effort to test the claim that the variance in the daily stock price changes for stock 1 is different from the variance in the daily stock price changes for stock 2, the investor obtains a random sample of 21 daily price changes for stock 1 and 21 daily price changes for stock 2. 

The summary statistics associated with these samples are: n
1 = 21, s
1 = .725, n
2 = 21, s
2 = .529. 

If you compute the test value by placing the larger variance in the numerator, at the .05 level of significance, would you conclude that the risks associated with these two stocks are different? 

 
 
 
 

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Question 3 of 17
1.0 Points
Which of the following statements is true regarding the F – distribution?

 
 
 
 

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Part 2 of 8 –
 
Question 4 of 17
1.0 Points

 

The marketing manager of a large supermarket chain would like to use shelf space to predict the sales of pet food. For a random sample of 12 similar stores, she gathered the following information regarding the shelf space, in feet, devoted to pet food and the weekly sales in hundreds of dollars. 
 

 

Store
1
2
3
4
5
6
Shelf Space
5
5
5
10
10
10
Weekly Sales
1.6
2.2
1.4
1.9
2.4
2.6

 

 

 

Store
7
8
9
10
11
12
Shelf Space
15
15
15
20
20
20
Weekly Sales
2.3
2.7
2.8
2.6
2.9
3.1

 

What is the estimated regression equation?

 
 
 
 

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Question 5 of 17
1.0 Points
The standard error of the estimate, s
est, is essentially the

 
 
 
 

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Question 6 of 17
1.0 Points
The correlation value ranges from

 
 
 
 

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Question 7 of 17
1.0 Points
In a simple linear regression analysis, the following sum of squares are produced: 

f$sum{(y- ar{y})^{2}}f$= 500

f$sum{(y-y')^{2}}f$= 100

f$sum{(y'- ar{y})^{2}}f$= 400

The proportion of the variation in Y that is explained by the variation in X is:

 
 
 
 

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Question 8 of 17
1.0 Points
If an estimated regression line has a Y-intercept of –7.5 and a slope of 2.5, then when X = 3, the actual value of Y is:

 
 
 
 

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Part 3 of 8 –
 
Question 9 of 17
2.0 Points
Accepted characters: numbers, decimal point markers (period or comma), sign indicators (-), spaces (e.g., as thousands separator, 5 000), “E” or “e” (used in scientific notation). 
NOTE: For scientific notation, a period MUST be used as the decimal point marker. 

Complex numbers should be in the form (a + bi) where “a” and “b” need to have explicitly stated values. 

For example: {1+1i} is valid whereas {1+i} is not. {0+9i} is valid whereas {9i} is not. 

A business major wants to determine whether the variation in advertising costs of hair salons is different from the variation in advertising costs of nail salons.  He surveys several businesses and finds the standard deviation in monthly advertising costs is $23 for 12 hair salons, and $43 for 8 nail salons.

What is the test value for this hypothesis test?

Test value: 

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Part 8 of 8 –
 
Question 16 of 17
1.0 Points
If there is no linear relationship between two variables X and Y, the coefficient of determination, R
2, must be 
f$pm f$1.0.

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Question 17 of 17
1.0 Points
In every regression study there is a single variable that we are trying to explain or predict. This is called the response variable or dependent variable.

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