App stat questions

Case 1

The following is part of an ANOVA table that was obtained from data regarding three treatments and a total of 15 observations.

Source of

Variation

Sum of

Squares

Degrees of

Freedom

Between Treatments

Error (Within Treatments)

Refer to case 1 . The number of degrees of freedom corresponding to between treatments is

Question 1 options:

	12
	2
	3
	4

Refer to case 1 . The mean square between treatments (MSTR) is

Question 2 options:

	36
	16
	8
	32

Refer to case 1 . The number of degrees of freedom corresponding to within treatments is

Question 3 options:

	12
	2
	3
	15

Refer to case 1. The computed F test statistics is

Question 4 options:

	32
	8
	0.667
	4

Refer to Case 1. If at 95% confidence, we want to determine whether or not the means of the populations are equal, using Excel the p-value is

Question 5 options:

	TDIST (F, df1,df2)
	FDIST(t,df1,df2)
	FDIST (F,df1,df2)
	None of these alternatives is correct

Refer to Case 1 . If p-value between 0.05 to 0.1

the conclusion of the test is that the means

Question 6 options:

	are equal
	may be equal
	are not equal
	None of these alternatives is correct.

Case 2 Case 2

The following information regarding a dependent variable Y and an independent variable X is provided

Refer to case 2. The total sum of squares (SST) is

Case 2

Question 7 options:

	-156
	234
	1870
	1974

Refer to case 2. The sum of squares due to error (SSE) is

Question 8 options:

	-156
	234
	1870
	1974

Refer to case 2. The mean square error (MSE) is

Question 9 options:

	1870
	13
	1974
	935

Refer to case 2. The slope of the regression equation is

Question 10 options:

	-0.667
	0.667
	100
	-10

Refer to case 2. The Y intercept is

Question 11 options:

-0.667

0.667

100

-100

Refer to case 2. The coefficient of correlation is

Question 12 options:

-0.2295

0.2295

0.0527

-0.0572

Case 3

In order to determine whether or not the number of automobiles sold per day (Y) is related to price (X1 in $1,000), and the number of advertising spots (X2), data were gathered for 7 days. Part of the regression results is shown below.

	Coefficient	Standard Error
Intercept	0.8051
X1	0.4977	0.4617
X2	0.4733	0.0387
Analysis of Variance
Source of	Degrees	Sum of	Mean
Variation	of Freedom	Squares	Square	F
Regression		40.700
Error		1.016

Determine the least squares regression function relating Y to X1 and X2.

Question 13 options:

	y-estimated=7.017-8.6233X1+0.0858X2
	y-estimated=-7.0174+8.6233X1+0.0858X2
	y-estimated=7.0174+8.6233X1+0.0858X2
	non of these alternatives is correct

Refer to case 3

If the company charges $20,000 for each car and uses 10 advertising spots, how many cars would you expect them to sell in a day?

Question 14 options:

	15 (rounded from 15.49)
	16
	17
	14

Refer to case 3

At a = 0.05, test to determine if the equation developed represents a significant relationship between the independent variables and the dependent variable.

The test statistics is

Question 15 options:

	F
	t
	We can use F or t
	None of these alternatives is correct.

Refer to test 3

At a = 0.05, test to determine if the fitted equation developed in Part a represents a significant relationship between the independent variables and the dependent variable.

to find p-value we should use excel function

Question 16 options:

	p-value is FDIST (F,df1,df2)
	p-value is FDIST (t,df1,2)
	p-value is FDIST (t,df2,2)
	None of these alternatives is correct

Refer to case 3. At a = 0.05, test to determine if the fitted equation developed in Part a represents a significant relationship between the independent variables and the dependent variable.

Conclusion is

Question 17 options:

	F = 80.12; p-value > .01; Don’t reject H0 The model is not significant at alpha 0.05
	F = 8.12
	F = 80.12; p-value < .01 (almost zero); reject H0 and conclude that te model is significant at alpha 0.05
	None of these alternatives is correct.

Refer to case 3

At 95% confidence, test to see if price is a significant variable.

Use test statistics

Question 18 options:

	F
	t
	both t and F
	None of these alternatives is correct.

Refer to case 3. At 95% confidence, test to see if price is a significant variable.

Conclusion is

Question 19 options:

	t = 0.008; p-value less than alpha . Reject H0; price is a significant variable at alpha 0.05
	t = 1.078; p-value is between 0.1 and 0.2; do not reject H0; price is not a significant variable at 95% confidence.
	t = 1.078; p-value is less than 0.1 ; reject H0 price is a significant variable at 95% confidance
	None of these alternatives is correct.

Refer to case 3

Determine the multiple coefficient of determination

and interpret this number

Question 20 options:

	0.9756. 97.56% of the variation of the number of automobiles sold per day is explained by the variation in price and the number of advertising spots.
	0.9756 97.56% of the variation of the number of automobiles sold per day is explained by the variation in price.
	0.3467 34.67% of the variation of the number of automobiles sold per day is explained by the variation in price.
	0.7654 76.54% of the variation of the number of automobiles sold per day is explained by the variation in the number of advertising spots.

admin