Regression analysis for Barton Industries results in the following output. Coefficients Y Intercept 10,200.00 X Variable...
Regression analysis for Barton Industries results in the following output.
|
Coefficients |
|
|
Y Intercept |
10,200.00 |
|
X Variable |
345.00 |
Assume Barton Industries will produce 500 units next month. What are the total estimated production costs for the month?
| $162,300 |
| $5,099,655 |
| $5,100,345 |
| $182,700 |
Homework Answers
y = a+bx
Estimated production costs for 500 units
= 10,200 + (345*500)
= 182,700
Option D is the answer
Add Answer to:
Regression analysis for Barton Industries results in the
following output.
Coefficients
Y Intercept
10,200.00
X Variable...
Regression Analysis 2 You run a regression analysis and receive the following results SUMMARY OUTPUT Regression...
Regression Analysis 2 You run a regression analysis and receive the following results SUMMARY OUTPUT Regression Statistics Multiple R 0 .9697622171 R Square 0.940438758 Adjusted R Square 0.92058501 Standard Error 360.0073099 Observations 5 IIIIIIII ANOVAT di SS M S F Sanificance Regression 11 6 139184 2116139184 2111 47 368327870 000 Residual 3 3 88.815.78951129605,26321 Total 146528000T IUSTI Intercept X Variable 1 Coefficients 2056. 58 1.50 Standard Error 4 54.25 0.1816 Stat 6.728812231 .882465029 P-value 0006701290 0.006283174 Refer to the Regression...
7. The following shows a partial printout of a regression analysis: Intercept X Variable 1 Coefficients...
7. The following shows a partial printout of a regression analysis: Intercept X Variable 1 Coefficients 6903.83329 3.02097535 Which of the following statement about this regression analysis is correct? a. The fixed cost component is $6,903. b. The variable cost per unit is $3.02. c. Projected total cost for 400 units of activity will be $8,111. d. All of the above. 8. Regression analysis: a. is always accurate. b. uses statistical techniques. c. may involve more than one predictor variable....
Q 10: Shown below is a portion of an Excel output for regression analysis relating Y...
Q 10: Shown below is a portion of an Excel output for regression analysis relating Y (dependent variable) and X (independent variable). Degrees of Freedom Regression 205 Residual 53.28 Total 341.33 SS Coefficients Standard Error t Stat p-value Intercept 53.90 6.7105 8.0379 0.001 Volume 4.06 0.8724 4.6505 0.009 the estimated regression equation that relates (Y) to (X)? ce the coefficient of determination between Y and X. e result.
Return to questio Answer is complete but not entirely correct. Intercept X Variable 1 Coefficients 3,449.37...
Return to questio Answer is complete but not entirely correct. Intercept X Variable 1 Coefficients 3,449.37 8.77 6. Using the regression output, create a linear equation (y = a + bx) for estimating Leslie's operating costs. (Round your answers to 2 decimal places.) Answer is complete but not entirely correct. (Number of $ 3,449.37 - 8.77 $ Jerseys) Total Cost 7. Using the least squares regression results, calculate the store's expected operating cost if it prints 605 jerseys, (Round your...
1st regression analysis 2nd regression analysis 1. Analyze the two regression analysis's above ...
1st regression analysis
2nd regression analysis
1. Analyze the two regression analysis's above and make
a recommendation on if the organization should increase, decrease,
or retain their pricing and why?
2. What happens to the dependent variable Y if the price
X1 decreases in the second regression analysis?
SUMMARY OUTPUT Y=UNITS SOLD X=PRICE Regression Statistics Multiple R R Square Adiusted R S Standard Error Observations 0.874493978 0.764739718 0.756026374 159.2178137 29 quare ANOVA df MS Significance F 1 2224908.261 2224908.26187.76650338 5.64792E-10...
O 10 an relatin sile) and shown below is, Excel output for portion of analysis Y...
O 10 an relatin sile) and shown below is, Excel output for portion of analysis Y Celependent regression Cdependent vari Cinde pendent variable) х ANOVA df Regression 3338,312 Residual 1 2036.195 Total 9 14514.400 coefficients standad tstat P-value error Intercept 241.67 83.280 1.684 0.030 148.27 38-312 1.283 0.035 a) what is the estimated equation that relates y regression +o b) what is the estimated value of Y if x = 3.5? c) Compute the value of the coefficient determination and...
BUSINESS STATISTICS Shown below is a portion of a computer output for a regression analysis relating...
BUSINESS STATISTICS
Shown below is a portion of a computer output for a regression analysis relating demand (y in thousands of units) and unit price (x in thousands of dollars). ANOVA SS 5048.818 Regression Residual Total 8181.479 Standard Error Intercept Coefficients 80.390 -2.137 What is the value of sample correlation coefficient? O 0.7856 0 -0.6171 0 0.6171 0 -0.7856
please answer all question fully Statistical Analysis: The regression output presented on the next page was...
please answer all question fully
Statistical Analysis: The regression output presented on the next page was obtained from regressing the dependent variable Y on the independent variable L. The variable Y is real gross domestic product measured in billions of year 2009 dollars. The labor variable L is the number of full time equivalent employees measures in thousands of employees 5. Present these regression results in a professional manner, as demonstrated in class. (10 points) Provide an economic interpretation of...
An important application of regression analysis in accounting is in the estimation of cost. By collecting...
An important application of regression analysis in accounting is
in the estimation of cost. By collecting data on volume and cost
and using the least squares method to develop an estimated
regression equation relating volume and cost, an accountant can
estimate the cost associated with a particular manufacturing
volume. Consider the following sample of production volumes and
total cost data for a manufacturing operation.
Production Volume (units)
Total Cost ($)
400
3800
500
4300
600
5300
650
5900
750
6300...
4. Part of an Excel output relating X (independent variable) and Y (dependent variable) is shown...
4. Part of an Excel output relating X (independent variable) and Y (dependent variable) is shown below. Fill in all the blanks marked with "?". Summary Output Regression Statistics Multiple R ? R Square ? Adjusted R Square 0.8125 Standard Error 1.3693064 Observations 7 ANOVA df SS MS F Significance F Regression ? 50.625 ? ? ? Residual ? 9.375 ? Total 6 60 Coefficients Standard Error. t Stat P-value Lower 95% Intercept 13.75 1.398341. 9.833082 0.0001853 10.15555 x -1.125...
Regression Analysis 2 You run a regression analysis and receive the following results SUMMARY OUTPUT Regression Statistics Multiple R 0 .9697622171 R Square 0.940438758 Adjusted R Square 0.92058501 Standard Error 360.0073099 Observations 5 IIIIIIII ANOVAT di SS M S F Sanificance Regression 11 6 139184 2116139184 2111 47 368327870 000 Residual 3 3 88.815.78951129605,26321 Total 146528000T IUSTI Intercept X Variable 1 Coefficients 2056. 58 1.50 Standard Error 4 54.25 0.1816 Stat 6.728812231 .882465029 P-value 0006701290 0.006283174 Refer to the Regression...
7. The following shows a partial printout of a regression analysis: Intercept X Variable 1 Coefficients 6903.83329 3.02097535 Which of the following statement about this regression analysis is correct? a. The fixed cost component is $6,903. b. The variable cost per unit is $3.02. c. Projected total cost for 400 units of activity will be $8,111. d. All of the above. 8. Regression analysis: a. is always accurate. b. uses statistical techniques. c. may involve more than one predictor variable....
Q 10: Shown below is a portion of an Excel output for regression analysis relating Y (dependent variable) and X (independent variable). Degrees of Freedom Regression 205 Residual 53.28 Total 341.33 SS Coefficients Standard Error t Stat p-value Intercept 53.90 6.7105 8.0379 0.001 Volume 4.06 0.8724 4.6505 0.009 the estimated regression equation that relates (Y) to (X)? ce the coefficient of determination between Y and X. e result.
Return to questio Answer is complete but not entirely correct. Intercept X Variable 1 Coefficients 3,449.37 8.77 6. Using the regression output, create a linear equation (y = a + bx) for estimating Leslie's operating costs. (Round your answers to 2 decimal places.) Answer is complete but not entirely correct. (Number of $ 3,449.37 - 8.77 $ Jerseys) Total Cost 7. Using the least squares regression results, calculate the store's expected operating cost if it prints 605 jerseys, (Round your...
1st regression analysis
2nd regression analysis
1. Analyze the two regression analysis's above and make
a recommendation on if the organization should increase, decrease,
or retain their pricing and why?
2. What happens to the dependent variable Y if the price
X1 decreases in the second regression analysis?
SUMMARY OUTPUT Y=UNITS SOLD X=PRICE Regression Statistics Multiple R R Square Adiusted R S Standard Error Observations 0.874493978 0.764739718 0.756026374 159.2178137 29 quare ANOVA df MS Significance F 1 2224908.261 2224908.26187.76650338 5.64792E-10...
O 10 an relatin sile) and shown below is, Excel output for portion of analysis Y Celependent regression Cdependent vari Cinde pendent variable) х ANOVA df Regression 3338,312 Residual 1 2036.195 Total 9 14514.400 coefficients standad tstat P-value error Intercept 241.67 83.280 1.684 0.030 148.27 38-312 1.283 0.035 a) what is the estimated equation that relates y regression +o b) what is the estimated value of Y if x = 3.5? c) Compute the value of the coefficient determination and...
BUSINESS STATISTICS
Shown below is a portion of a computer output for a regression analysis relating demand (y in thousands of units) and unit price (x in thousands of dollars). ANOVA SS 5048.818 Regression Residual Total 8181.479 Standard Error Intercept Coefficients 80.390 -2.137 What is the value of sample correlation coefficient? O 0.7856 0 -0.6171 0 0.6171 0 -0.7856
please answer all question fully
Statistical Analysis: The regression output presented on the next page was obtained from regressing the dependent variable Y on the independent variable L. The variable Y is real gross domestic product measured in billions of year 2009 dollars. The labor variable L is the number of full time equivalent employees measures in thousands of employees 5. Present these regression results in a professional manner, as demonstrated in class. (10 points) Provide an economic interpretation of...
An important application of regression analysis in accounting is
in the estimation of cost. By collecting data on volume and cost
and using the least squares method to develop an estimated
regression equation relating volume and cost, an accountant can
estimate the cost associated with a particular manufacturing
volume. Consider the following sample of production volumes and
total cost data for a manufacturing operation.
Production Volume (units)
Total Cost ($)
400
3800
500
4300
600
5300
650
5900
750
6300...
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