HomeworkLib
Question

Consider the following excel regression analysis output. Explain the significance of the r, p, F value; Give the regression e
math   Statistics-And-Probability   
0 0
Add a comment Improve this question Transcribed image text
Next > < Previous
Sort answers by oldest

Homework Answers

Answer #1

Date a lnes and the obser vee th고 rty A 2. A e 為→

0 0
Add a comment
Know the answer?
Add Answer to:
Consider the following excel regression analysis output. Explain the significance of the r, p, F value;...
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Log In

Sign Up

Not the answer you're looking for? Ask your own homework help question. Our experts will answer your question WITHIN MINUTES for Free.
Similar Homework Help Questions

  • Dep.= % WRK Indep.= % MGT SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R...

    Dep.= % WRK Indep.= % MGT SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Significance df SS MS F F Regression 102.1488 148.9539 Residual Total 12.0000 Standard Coefficients Error t Stat P-value Lower 95% Upper 95% Intercept % MGT 0.4543 SE CI CI PI PI Predicted Predicted Lower Upper Lower Upper x0 Value Value 95% 95% 95% 95% 67.0000 67.8474 65.8779 69.8169 72.0000 70.1189 68.2003 72.0375 76.0000 71.9361 69.7884 74.0838 Dep.= % MGT...

  • Regression Statistics Multiple R 0.88012 R Square 0.77461 Adjusted R Square 0.77190 Standard Error 56.6927 Observations...

    Regression Statistics Multiple R 0.88012 R Square 0.77461 Adjusted R Square 0.77190 Standard Error 56.6927 Observations 253 ANOVA Significance 285.2516 MS 916816.787 3214.0637 Regression Residual Total 0.000 2750450.3598 800301.8665 3550752.226 252 Intercept Income Coefficients Standard Error 70.2382 15.8338 5.45850 .2485 t Stat P-value 4.4360 0.000014 21.96960 .000 Lower 3 9.053 4.969 "pper 95% 1.4234 479 HULLU LIIS TILIR. SUMMARY OUTPUT Regression Statistics Multiple R 0.8778 R Square Adjusted R Square 0.6558 Standard Error Observations ANOVA ANOVA Significance Regression 45.3528 de...

  • Linear Regression: Use Data Analysis in Excel to conduct the Regression Analysis to reproduce the excel...

    Linear Regression: Use Data Analysis in Excel to conduct the Regression Analysis to reproduce the excel out put below (Note: First enter the data in the next page in an Excel spreadsheet) Home Sale Price: The table below provides the Excel output of a regression analysis of the relationship between Home sale price(Y) measured in thousand dollars and Square feet area (x):   SUMMARY OUTPUT Dependent: Home Price ($1000) Regression Statistics Multiple R 0.691 R Square 0.478 Adjusted R Square 0.465...

  • Figure 2 Regression Output SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard...

    Figure 2 Regression Output SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.921261 0.848722 0.8055 0.711125 10 ANOVA Significance MS 0.001347 Regression Residual Total 19.86011 9.930053 19.63628 3.539894 0.505699 23.4 Standard Error Upper 95% Coefficients 0.20018 2.211198 0.07185 tStat P-value Lower 95% Intercept Size (cubic Metres) Weight (00's kg 2.19481 1.794453 0.676122 3.270412 0.013667 0.612423 3.809974 0.47295 0.329255 0.84353 -0.23731 0.819212 0.169626 0.42356 0.684594 (a)Based on the above regression output, interpret the regression coefficients...

  • In relation to the below output from the Regression Analysis of the S&P/ASX200 Index (X) and...

    In relation to the below output from the Regression Analysis of the S&P/ASX200 Index (X) and from the company ABC Shares derived from weekly data over a 12 month period, can you please explain the key measures and what this all means eg. Number of Observations, R Square, Value of the Slope and the P-Value of the Slope etc. SUMMARY OUTPUT Regression Statistics Multiple R 0.045274332 R Square 0.002049765 Adjusted R Square -0.01790924 Standard Error 0.023996449 Observations 52 ANOVA df...

  • HW # 5 Linear Regression: Use Data Analysis in Excel to conduct the Regression Analysis to...

    HW # 5 Linear Regression: Use Data Analysis in Excel to conduct the Regression Analysis to reproduce the excel out put below (Note: First enter the data in the next page in an Excel spreadsheet) Home Sale Price: The table below provides the Excel output of a regression analysis of the relationship between Home sale price(Y) measured in thousand dollars and Square feet area (x):    SUMMARY OUTPUT Dependent: Home Price ($1000) Regression Statistics Multiple R 0.691 R Square 0.478 Adjusted...

  • Dep.- WRK Indep.- MGT SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted RSquare Standard Error...

    Dep.- WRK Indep.- MGT SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted RSquare Standard Error Observations ANOVA Regression 102.1488 Residual Total 12.00001 Standard Coefficients P.valuell Lower 95 Upper 9524 LUV Upper 95 Intercept 6 MGT 0.4543 Predicted Predicted Lower Upper Lower XO Value Value 67.0000 65.8779 69.8169 72.0000 67.8474 70.1189 71.9361 68.2003 22.0375 74,0828 76.0000 69.7884 Dep.-% MGT Indep96 WRK SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations Observations ANOVA Regression 460.8873 148.9539...

  • Have I correctly calculated R squared in this problem? SUMMARY OUTPUT Regression Statistics Multiple R R...

    Have I correctly calculated R squared in this problem? SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.9241 0.9222 1425.3397 200 ANOVA Significance df MS Regression Residual Total 479410417802.47 95882083560.49 472.4892 39368362197.53 518778780000.00 0.00 194 199 202929702.05 Upper 95% CoefficientsStandard Erro t Stat P-value Lower 95% 45482.366 -10383.543 11.088 738.388 0.014 2.546 19403.8863 3153.7202 10.4859 175.8223 0.0023 1.2209 2.340.0201 Intercept V1 v2 7217.90 83746.83 -3.290.0012 16602.68 -4164.41 31.77 391.67 1085.11 0.02 0.14 1.06 0.2916...

  • 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...

  • Interpreting Regression Output Rikki Bake, the controller for XYZ Incorporated, suspects that factory overhead costs are...

    Interpreting Regression Output Rikki Bake, the controller for XYZ Incorporated, suspects that factory overhead costs are driven by the number of machine hours used. Using Excel, Ms. Bake input twelve months of historical data for total factory overhead costs and machine hours used. The summary output information is provided below. Use the output information provided to develop a cost formula for overhead cost. SUMMARY OUTPUT 4 Regression Statistics Multiple R 0.963809718 R Square 0.928929173 Adjusted R Square 0.92182209 Standard Error...

ADVERTISEMENT
Free Homework Help App
Download From Google Play
Scan Your Homework
to Get Instant Free Answers
Need Online Homework Help?
Ask a Question
Get Answers For Free
Most questions answered within 3 hours.
ADVERTISEMENT
ADVERTISEMENT