Which equation most closely represents the curve of best fit for thefollowing data?{(63, 50), (57, 68), (59, 55), (48, 71), (54, 72)}Oy -0.14x² +14.24x 283.69Oy = 0.88x -0.14Oy -0.14a + 14.24Oy=0.72x² 1.52x+148.39

Answered: Image /qna-images/answer/42cc103a-e153-4e76-8c13-6abc5daf85f3.jpg

Which equation most closely represents the curve of best fit for the Ollowing data? {(63, 50), (57, 68), (59, 55), (48, 71), (54, 72)} y=-0.14x2 + 14.24x 283.69 O y = 0.88x -0.14 Oy=-0.14x + 14.24 Oy=0.72x² 1.52x+148.39 -

Which equation most closely represents the curve of best fit for the Ollowing data? {(63, 50), (57, 68), (59, 55), (48, 71), (54, 72)} y=-0.14x2 + 14.24x 283.69 O y = 0.88x -0.14 Oy=-0.14x + 14.24 Oy=0.72x² 1.52x+148.39 -

Algebra and Trigonometry (6th Edition)

6th Edition

ISBN:9780134463216

Author:Robert F. Blitzer

Publisher:Robert F. Blitzer

ChapterP: Prerequisites: Fundamental Concepts Of Algebra

Section: Chapter Questions

Problem 1MCCP: In Exercises 1-25, simplify the given expression or perform the indicated operation (and simplify,...

See similar textbooks

Similar questions

The line of best fit through a set of data is y=29.267+0.881xAccording to this equation, what is the predicted value of the dependent variable when the independent variable has value 60?y =
The accompanying table shows results from regressions performed on data from a random sample of 21 cars. The response (y) variable is CITY (fuel consumption in mi/gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi/gal). The equation CITY = -3.14 +0.816HWY was previously determined to be the best for predicting city fuel consumption. A car weighs 2740 lb, it has an engine displacement of 1.5 L, and its highway fuel consumption is 40 mi/gal. What is the best predicted value of the city fuel consumption? Is that predicted value likely to be a good estimate? Is that predicted value likely to be very accurate? Click the icon to view the table of regression equations. Regression Table The best predicted value of the city fuel consumption is (Type an integer or a decimal. Do not round.) Predictor (x) Variables WT/DISP/HWY WT/DISP WT/HWY DISP/HWY WT DISP HWY P-Value R² 0.000 0.943 0.000 0.748 0.000 0.942…
The following table gives the data for the grades on the midterm exam and the grades on the final exam. Determine the equation of the regression line, yˆ=b0+b1x�^=�0+�1�. Round the slope and y-intercept to the nearest thousandth. Grades on Midterm and Final Exams Grades on Midterm 7171 6262 7878 9494 8383 8181 8080 9494 8585 6262 Grades on Final 8888 7979 8888 9191 8080 7070 7171 9393 6565 7777
A regression was run to determine if there is a relationship between hours of tv watched per day (x) and number of sit-ups a person can do (y)
10) A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-0.767 b=31.009 r2=0.609961 r=-0.781 Use this to predict the number of situps a person who watches 7.5 hours of TV can do (to one decimal place)
The line of best fit through a set of data is ý = 14.714 – 3.985x According to this equation, what is the predicted value of the dependent variable when the independent variable has value 180? Round to 1 decimal place.
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-1.145 b=20.742 r?=0.508369 r=-0.713 Use this to predict the number of situps a person who watches 2.5 hours of TV can do (to one decimal place)
The following table gives the data for the grades on the midterm exam and the grades on the final exam. Determine the equation of the regression line, yˆ=b0+b1xy^=b0+b1x. Round the slope and y-intercept to the nearest thousandth. Grades on Midterm and Final Exams Grades on Midterm 78 63 85 92 82 89 69 89 83 61 Grades on Final 77 75 88 92 86 86 80 85 77 63
The accompanying table shows results from regressions performed on data from a random sample of 21 cars. The response (y) variable is CITY (fuel consumption in mi/gal). The predictor (x) variables are WT (weight in pounds), DISP (engine displacement in liters), and HWY (highway fuel consumption in mi/gal). The equation CITY = -3.14 +0.818HWY was previously determined to be the best for predicting city fuel consumption. A car weighs 2760 lb, it has an engine displacement of 2.2 L, and its highway fuel consumption is 34 mi/gal. What is the best predicted value of the city fuel consumption? Is that predicted value likely to be a good estimate? Is that predicted value likely to be very accurate? Click the icon to view the table of regression equations. The best predicted value of the city fuel consumption is (Type an integer or a decimal. Do not round.) Regression Table Predictor (x) Variables P-Value R² Adjusted R² WT/DISP/HWY WT/DISP WT/HWY DISP/HWY 0.000 0.943 0.000 0.747 0.000 0.941…
A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: ý = bo + bịx bo = 36.465 - 1.082 b1 - 0.646 Use this to predict the number of situps a person who watches 2.5 hours of TV can do (to one decimal place)
The equation of the line containing the points (−2,−4) and (2,5) is y=2.25x+0.5. Compute the sum of the squared residuals of the given data set for this line. The sum of the squared residuals for the line containing the points (−2,−4) and (2,5) is
The line of best fit through a set of data is y = - 42.824 – 3.033x According to this equation, what is the predicted value of the dependent variable when the independent variable has value 90? y = Round to 1 decimal place.