Question

True or false: at the 5% level of confidence the intercept is significantly different from zero?...

True or false: at the 5% level of confidence the intercept is significantly different from zero? 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 Depth 11.8072 0.790904 14.92874 5.69E-06 9.87193 13.74248 9.87193 13.74248 Well Age -2.23683 0.435949 -5.13093 0.002155 -3.30356 -1.1701 -3.30356 -1.1701 True False

Homework Answers

Answer #1

At the 5% level of confidence the intercept is significantly different from zero: False

Explanation:

Null Hypothesis H0: Intercept = 0 (Intercept is not significantly different from zero)

Alternate Hypothesis Ha: Intercept ≠ 0 (Intercept is significantly different from zero)

P-value corresponding to Intercept is 0.082583. Since p-value is greater than α = 0.05. So we fail to reject null hypothesis. This, intercept is not significantly different from zero at 5% level of confidence. Thus, statement given is False

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
Slightly different question. True or false: The effect of Well Age is significantly different than -2...
Slightly different question. True or false: The effect of Well Age is significantly different than -2 at the 5% level. That's right I asked about -2 not 0, so you cannot use the p-value printed in the table because that is a test of the estimate being equal to zero. 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...
Can weight of a vehicle significantly predict fuel economy? How can you tell? (Include statistic and...
Can weight of a vehicle significantly predict fuel economy? How can you tell? (Include statistic and level of significance/p value) Write an APA statement with the findings from this regression analysis. Regression Statistics Multiple R 0.045643559 R Square 0.002083334 Adjusted R Square -0.05335648 Standard Error 10.03995374 Observations 20 ANOVA df SS MS F Significance F Regression 1 3.78791868 3.78791868 0.037578 0.848463 Residual 18 1814.41208 100.800671 Total 19 1818.2 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0%...
Compare the two regression models. Does it make sense that spending and household debt could each...
Compare the two regression models. Does it make sense that spending and household debt could each be predicted by annual household income? Why or why not? 1. Predicting spending by household income Regression Statistics Multiple R 0.859343186 R Square 0.738470711 Adjusted R Square 0.737149856 Standard Error 1602.157625 Observations 200 ANOVA df SS MS F Significance F Regression 1 1435121315 1435121315 559.085376 1.42115E-59 Residual 198 508247993.2 2566909.056 Total 199 1943369308 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower...
Discuss the model and interpret the results: report overall model fit (t and significance), report the...
Discuss the model and interpret the results: report overall model fit (t and significance), report the slope coefficient and significance, report and interpret r squared. Regression Statistics Multiple R 0.001989374 R Square 3.95761E-06 Adjusted R Square -0.005046527 Standard Error 8605.170404 Observations 200 ANOVA df SS MS F Significance F Regression 1 58025.4985 58025.4985 0.00078361 0.977695901 Residual 198 14661693620 74048957.68 Total 199 14661751645 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 15668.85874 2390.079111 6.555790838...
Calculate the following statistics given the existing information (1 point per calculation): Regression Statistics Multiple R...
Calculate the following statistics given the existing information (1 point per calculation): Regression Statistics Multiple R R Square Adjusted R Square 0.559058 Standard Error Observations 30 ANOVA df SS MS F Significance F Regression 2 3609132796 19.38411515 6.02827E-06 Residual 27 2513568062 Total 29 6122700857 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept -15800.8 57294.51554 -0.27578 0.784814722 CARAT 12266.83 1999.250369 6.135715 1.48071E-06 DEPTH 156.686 928.9461882 0.168671 0.867312915 Additionally interpret your results. Be sure to comment on Accuracy, significance...
Regression Statistics Multiple R 0.710723 R Square 0.505127 Adjusted R Square 0.450141 Standard Error 1.216847 Observations...
Regression Statistics Multiple R 0.710723 R Square 0.505127 Adjusted R Square 0.450141 Standard Error 1.216847 Observations 21 ANOVA df SS MS F Significance F Regression 2 27.20518 13.60259 9.186487 0.00178 Residual 18 26.65291 1.480717 Total 20 53.8581 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 58.74307 12.66908 4.636728 0.000205 32.12632 85.35982 32.12632 85.35982 High School Grad -0.00133 0.000311 -4.28236 0.000448 -0.00198 -0.00068 -0.00198 -0.00068 Bachelor's -0.00016 5.46E-05 -3.00144 0.007661 -0.00028 -4.9E-05 -0.00028 -4.9E-05...
SUMMARY OUTPUT Regression Statistics Multiple R 0.84508179 R Square 0.714163232 Adjusted R Square 0.704942691 Standard Error...
SUMMARY OUTPUT Regression Statistics Multiple R 0.84508179 R Square 0.714163232 Adjusted R Square 0.704942691 Standard Error 9.187149383 Observations 33 ANOVA df SS MS F Significance F Regression 1 6537.363661 6537.363661 77.4535073 6.17395E-10 Residual 31 2616.515127 84.40371378 Total 32 9153.878788 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 61.07492285 3.406335763 17.92980114 6.41286E-18 54.12765526 68.02219044 54.12765526 68.02219044 Time (Y) -0.038369095 0.004359744 -8.800767426 6.17395E-10 -0.047260852 -0.029477338 -0.047260852 -0.029477338 Using your highlighted cells, what is the equation...
According to the Data, is the regression a better fit than the one with the Dummy...
According to the Data, is the regression a better fit than the one with the Dummy variable, explain? Regression Statistics Multiple R 0.550554268 R Square 0.303110002 Adjusted R Square 0.288887757 Standard Error 2.409611727 Observations 51 ANOVA df SS MS F Significance F Regression 1 123.7445988 123.7445988 21.31238807 2.8414E-05 Residual 49 284.5052051 5.806228676 Total 50 408.2498039 Coefficients Standard Error t Stat P-value Lower 95% Intercept 5.649982553 1.521266701 3.713998702 0.000522686 2.592882662 U-rate 1.826625993 0.395670412 4.616534206 2.84144E-05 1.0314965 Multiple R 0.572568188 R Square...
interpret each coefficient estimate and discuss its significance using α = 0.01, α = 0.05 and...
interpret each coefficient estimate and discuss its significance using α = 0.01, α = 0.05 and α = 0.10. Use the concepts of strict and weak significance too SUMMARY OUTPUT Regression Statistics Multiple R 0.820140129 R Square 0.672629832 Adjusted R Square 0.658699186 Standard Error 235.4076294 Observations 50 ANOVA df SS MS F Significance F Regression 2 5351505.158 2675752.58 48.2841827 4.0125E-12 Residual 47 2604587.342 55416.752 Total 49 7956092.5 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper...
In models B through D, what seems to be the relationship between the burglary rate and...
In models B through D, what seems to be the relationship between the burglary rate and the percent of the 18-64 population who are young adults (18-24)? Select one: a. It is difficult to describe the relationship; the young adult variables were all significant at 5% in models B, C, and D, but the signs and sizes of the coefficients were very different between models. b. Conclusions about the relationship between young adults and the burglary rate are difficult to...
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT