App stat questions

Post ID: 3184368

Overview

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

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.