Question 9: Use the following regression results to answer the question below. Regression Statistics Multiple R 0.8851 R Square 0.7835 Adjusted R Square 0.7474 Standard Error 5.4006 Observations 8 ANOVA df SS MS F Regression 1 633.242 633.242 21.711 Residual 6 175.000 29.167 Total 7 808.242 Coefficients Standard Error t Stat P-value Intercept 5.93118 4.17721 1.41989 0.20545 Total Bill -2.71551 0.58279 -4.65952 0.00347 Which of the following is true? The correlation between x and y must be approximately -0.7835. The correlation between x and y must be approximately 0.8851. The correlation between x and y must be approximately -0.8851. The correlation between x and y must be approximately 0.7835.
Added by Eric E.
Close
Step 1
The question asks us to determine the correct statement about the correlation between x and y based on the given regression results. Show more…
Show all steps
Your feedback will help us improve your experience
Federico Castro and 100 other Intro Stats / AP Statistics educators are ready to help you.
Ask a new question
Labs
Want to see this concept in action?
Explore this concept interactively to see how it behaves as you change inputs.
Key Concepts
Recommended Videos
A multiple regression analysis produced the following tables. SUMMARY OUTPUT Regression Statistics Multiple R 0.978724022 R Square 0.957900711 Adjusted R Squa 0.952287472 Standard Error 67.67055418 Observations 18 ANOVA df SS MS F Significance F Regression 2 1562918.941 781459.5 170.6503 4.80907E-11 Residual 15 68689.55855 4579.304 Total 17 1631608.5 Coefficients Standard Error t Stat P-value Intercept 1959.709718 306.4905312 6.39403 1.21E-05 X1 -0.469657287 0.264557168 -1.77526 0.096144 X2 -2.163344882 0.278361425 -7.77171 1.23E-06 The sample size for this analysis is __________. A. 18 B. 17 C. 24 D. 12 E. 15
Adi S.
The regression output below is based on the number of Internet Ads and Total Sales for a local business. Determine the predicted amount of Total Sales if the local business runs 25 Internet Ads. SUMMARY OUTPUT Regression Statistics Multiple R 0.8489 R Square 0.7206 Adjusted R Square 0.6648 Standard Error 55.4177 Observations 7 ANOVA df SS MS F Regression 1 39623.23 39623.23 12.902 Residual 5 15355.62 3071.125 Total 6 54978.86 Coefficients Std. Error t Stat P-value Intercept 26.32 51.0396 -0.51575 0.6280 Internet Ads 9.51 2.64882 3.591916 0.0157
The data from exercise I follow. $$ \frac{x_{i}|1 \quad 2 \quad 3 \quad 4 \quad 5}{y_{i}|3 \quad 7 \quad 5 \quad 11 \quad 14} $$ The estimated regression equation for these data is $\hat{y}=.20+2.60 x$ $$ \begin{array}{l}{\text { a. Compute SSE, SST, and SSR using equations }(12.8),(12.9), \text { and }(12.10) .} \\ {\text { b. Compute the coefficient of determination } r^{2} \text { . Comment on the goodness of fit. }} \\ {\text { c. Compute the sample correlation coefficient. }}\end{array} $$
Recommended Textbooks
Elementary Statistics a Step by Step Approach
The Practice of Statistics for AP
Introductory Statistics
Transcript
18,000,000+
Students on Numerade
Trusted by students at 8,000+ universities
Watch the video solution with this free unlock.
EMAIL
PASSWORD