ZuoTi.Pro
Question

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 SS MS F Significance F
Regression 1 5.9137E-05 5.9137E-05 0.102698766 0.749950242
Residual 50 0.028791478 0.00057583
Total 51 0.028850615
Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
Intercept 0.004632539 0.003457195 1.33997042 0.186313054 -0.002311442 0.01157652 -0.002311442 0.01157652
PWR - S&P200 - X -0.081131103 0.253165645 -0.320466482 0.749950242 -0.589629266 0.427367059 -0.589629266 0.427367059
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

Y = 0.0046 - 0.0811*X

...........

number of observation = 52

R square = 0.0020

only 0.2 % of variation is explaine dby x

............

slope = -0.0811

p value for slope = 0.74995

p avlue > 0.0 5,

slope is no significant

....................

this modal is not a good fit modal and can not be used to predict Y

..................

Please let me know in case of any doubt.

Thanks in advance!


Please upvote!

0 0
Add a comment
Know the answer?
Add Answer to:
In relation to the below output from the Regression Analysis of the S&P/ASX200 Index (X) and...
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

  • What is the coefficient? What is the standard error? What is the z-statistic? Is the coefficient...

    What is the coefficient? What is the standard error? What is the z-statistic? Is the coefficient sufficiently different from zero? How about one? Explain. SUMMARY OUTPUT Regression Statistics Multiple R 0.58175248 R Square 0.33843594 Adjusted R S 0.31393357 Standard Err 1.1991813 Observations 29 ANOVA df SS MS Significance F 0.000932269 Regression 1 19.86268888 19.86268888 13.8123745 Residual 38.82696629 27 1.438035789 Total 58.68965517 28 Coefficients Standard Error P-value t Stat Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -0.0202247 0.223805467 -0.090367404...

  • 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...

  • Hi I was wondering if i could have some help with some distribution questions. 1. show...

    Hi I was wondering if i could have some help with some distribution questions. 1. show where zero and one fall on a normal distribution based on thedata. 2.is the coefficient sufficiently different than zero? explain 3. is the coefficient sufficiently different than one? explain. Regression Statistics Multiple R 0.806174983 0.649918103 R Square Adjusted R Square Standard Error Observations 0.636952107 13.57635621 29 ANOVA Significance F E SS MS df 9238.877183 9238.877 50.12481 1.30123E-07 Regression Residual 4976.571093 184.3174 27 14215.44828 Total...

  • We are doing regression analysis for business analytics class and I am having a hard time reading...

    We are doing regression analysis for business analytics class and I am having a hard time reading this data. Please help. SUMMARY OUTPUT Regression Statistics Multiple R 0.999964 R Square 0.999928 Adjusted R Square 0.9999248 Standard Error 267.074107 Observations 48 ANOVA df SS MS F Significance F Regression 2 44576676715 2.23E+10 312474.2 6.1672E-94 Residual 45 3209786.045 71328.58 Total 47 44579886501 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -42159057 121894.4727 -345.865 1.04E-78 -42404564.6...

  • SUMMARY OUTPUT Regression Statistics Multiple R 0.99806038 R Square 0.996124522 Adjusted R Square 0.995155653 Standard Error...

    SUMMARY OUTPUT Regression Statistics Multiple R 0.99806038 R Square 0.996124522 Adjusted R Square 0.995155653 Standard Error 387.1597665 Observations 16 ANOVA df SS MS F Significance F Regression 3 4.62E+08 1.54E+08 1028.131 9.91937E-15 Residual 12 1798712 149892.7 Total 15 4.64E+08 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 1946.802039 504.1819 3.861309 0.002263 848.2839829 3045.32 848.284 3045.32 XRay (x1) 0.038577091 0.013042 2.957935 0.011966 0.010161233 0.066993 0.010161 0.066993 BedDays (x2) 1.039391967 0.067556 15.38573 2.91E-09 0.892201042 1.186583...

  • Calculate the 95% prediction interval of y when x=5 using the 2000 pairs Mean of x...

    Calculate the 95% prediction interval of y when x=5 using the 2000 pairs Mean of x = 4.51 Regression Statistics Multiple R 0.012848 R Square 0.000165 Adjusted R Square -0.00034 Standard Error 2.869737 Observations 2000 ANOVA df SS MS F Significance F Regression 1 2.716416 2.716416 0.329847 0.565814 Residual 1998 16454.31 8.235388 Total 1999 16457.02 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 4.509054 0.119572 37.70997 1.7E-235 4.274555 4.743552574 4.274555 4.743553 X 0.012884...

  • What percent of the variance in well production is explained by knowing well depth and well...

    What percent of the variance in well production is explained by knowing well depth and well age? SUMMARY OUTPUT Regression Statistics Multiple R 0.98711 R Square 0.974387 Adjusted R Square 0.965849 Standard Error 47.4523 Observations 9 ANOVA df SS MS F Significance F Regression 2 513960.7 256980.4 114.1262 1.68E-05 Residual 6 13510.32 2251.72 Total 8 527471.1 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -100.805 48.43281 -2.08133 0.082583 -219.316 17.70612 -219.316 17.70612 Well...

  • Regression Statistics Multiple R 0.896755 R Square 0.80417 Adjusted R Square 0.767452 Standard Error 51.04855 Observations...

    Regression Statistics Multiple R 0.896755 R Square 0.80417 Adjusted R Square 0.767452 Standard Error 51.04855 Observations 20 ANOVA df SS MS F Significance F Regression 3 171220.5 57073.49 21.90118 6.56E-06 Residual 16 41695.28 2605.955 Total 19 212915.8 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 427.1938 59.60143 7.167509 2.24E-06 300.8444 553.5432 300.8444 553.5432 Temp (deg) -4.58266 0.772319 -5.93364 2.1E-05 -6.21991 -2.94542 -6.21991 -2.94542 Insulation (ins.) -14.8309 4.754412 -3.11939 0.006606 -24.9098 -4.75196 -24.9098 -4.75196...

  • 7,10,11 Based on the following regression output, what is the equation of the regression line? Regression...

    7,10,11 Based on the following regression output, what is the equation of the regression line? Regression Statistics Multiple R 0.917214 R Square 0.841282 Adjusted R Square 0.821442 Standard Error 9.385572 Observations 10 ANOVA df SS MS Significance F 1 Regression 3735.3060 3735.30600 42.40379 0.000186 8 Residual 704.7117 88.08896 9 Total 4440.0170 Coefficients Standard Error t Stat P-value Lower 95% Intercept 31.623780 10.442970 3.028236 0.016353 7.542233 X Variable 1.131661 0.173786 6.511819 0.000186 0.730910 o a. 9; = 7.542233+0.7309 Xli o b....

  • SUMMARY OUTPUT Regression Statistics Multiple R 0.985689515 R Square 0.97158382 Adjusted R Square 0.968940454 Standard Error...

    SUMMARY OUTPUT Regression Statistics Multiple R 0.985689515 R Square 0.97158382 Adjusted R Square 0.968940454 Standard Error 754.6653051 Observations 48 ANOVA df SS MS F Significance F Regression 4 837320651.9 209330163 367.555599 1.23563E-32 Residual 43 24489348.08 569519.723 Total 47 861810000 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -979.9824986 2587.408411 -0.3787506 0.70673679 -6197.988856 4238.02386 -6197.988856 4238.023859 Price (cents) -39.65930534 3.380682944 -11.731152 5.4685E-15 -46.47710226 -32.841508 -46.47710226 -32.84150842 Competitors  Price (cents) 39.71320378 3.717321495 10.6832847 1.1179E-13 32.21651052 47.209897...

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
ADVERTISEMENT