Chest size (inches) 49 42 D 385 Weight (pounds) Click the icon to view the critical values of the Pearson correlation coefficient r 36 56 50 39 296 570 501 353 487 What is the regression equation? ŷ=+x (Round to one decimal place as needed.) ...
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- Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported asy=20.41x+15.59y=20.41x+15.59and the r=0.272r=0.272.What proportion of the variation in y can be explained by the variation in the values of x?r² = %Report answer as a percentage accurate to one decimal place.Which of the following is the most appropriate equation to model the data? ŷ = –10.89x + 0.85 ŷ = –0.85x + 10.89 ŷ = 10.89(0.85)x ŷ = 0.85(10.89)xYou generate a scatter plot using Excel. You then have Excel plot the trend line and report the equation and the r2r2 value. The regression equation is reported asy=60.71x+33.51y=60.71x+33.51and the r2=0.1764r2=0.1764.What is the correlation coefficient for this data set?r =
- Use the value of the linear correlation coefficient to calculate the coefficient of determination. What does this tell you about the explained variation of the data about the regression line? About the unexplained variation?Help please!Using the data, run a regression where you control for “Promotion,” and test the effect of “Wins” on “Attendance”. Does “Promotion” have a significant effect on “Attendance”? Wins Promotion Attendance 4 29500 36300 6 55700 40100 6 71300 41200 8 87000 53000 6 75000 44000 7 72000 45600 5 55300 39000 7 81600 47500
- The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 41 inches. Is the result close to the actual weight of 153 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) Click the icon to view the critical values of the Pearson correlation coefficient r. 40 53 38 43 44 58 D 227 360 153 206 234 414 What is the regression equation? y=+x (Round to one decimal place as needed.) What is the best predicted weight of a bear with a chest size of 41 inches? The best predicted weight for a bear with a chest size of 41 inches is (Round to one decimal place as needed.) Is the result close to the actual weight of 153 pounds? O A. This result is exactly the same as the actual weight of the bear. O B. This result is close to the actual weight of the bear. O C. This result is very close to the actual weight of the bear. O D. This…helpInclude the explanation please.
- The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 44 inches. Is the result close to the actual weight of 293 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) 45 221 265 50 41 52 45 335 307 45 265 Critical Values of the Pearson Correlation Coefficient r 321 Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? Critical Values of the Pearson Correlation Coefficient r a = 0.05 a = 0.01 0.990 NOTE: To test Ho: p=0 y=+x (Round to one decimal place as needed.) 4 against H,: p#0, reject H, jf the absolute value of r is greater than the critical value in the table. 0.950 0.878 0.959 6 0.811 0.917 0.754 0.875 8 0.707 0.834 9 0.666 0.798 10 0.632 0.765 11 0.602 0.735 12 0.576 0.708 0.684 0.661 13 0.553 14 0.532 15 0.514 0.641 0.497 16 17 18 19 0.623…Bluereef real estate agent wants to form a relationship between the prices of houses, how many bedrooms, House size in sq ft and Lot Size in sq ft. The data pertaining to 100 houses were processed using MINITAB and the following is an extract of the output obtained: The regression equation is Price = B + ¢Bedroom + yHouse Size + ALot Size Predictor Coef SE Coef T P Constant 37718 14177 2.66 ** Bedrooms 2306 6994 0.33 0.742 House Size 74.3 52.98 0.164 Lot Size -4.36 17.02 -0.26 0.798 S= 25023 R-Sq=56.0% R-Sq (adj) =54.6% Source DF MS F P Regression Residual 76501718347 25500572782 *** **** Error 96 60109046053 626135896 Total 99 d) Is y significantly different from -0.5? e) Perform the F test at the 1% level, making sure to state the null and alternative hypotheses. f) Give an interpretation to the term “R-sq" and comment on its value.