Consider the data. X; 2 6 9 13 20 Y; 9 20 | 7 27 23 The estimated regression equation for these data is ŷ = 9.2 + 0.8x. What percentage of the total sum of squares can be accounted for by the estimated regression equation? (Round your answer t one decimal place.) % What is the value of the sample correlation coefficient? (Round your answer to three decimal places.)
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- Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. Height, x Stories, y A 60- 0 775 53 Q 619 47 519 46 OB. 508 42 Find the regression equation. y = x+ (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. Q. A. 60 0 491 37 800 800 Height (feet) (n) Brodict the value of x for x=503. Choose the correct answer below. Height (feet) 474 36 D ... (a) x = 503 feet (c) x 310 feet OC. 800 0 Height (feet) Q www. (b)x=642 feet (d) x = 730 feet OD. 60- 0- 0 800 Height (feet)The data show the number of viewers for television stars with certain salaries. Find the regression equation, letting salary be the independent (x) variable. Find the best predicted number of viewers for a television star with a salary of $7 million. Is the result close to the actual number of viewers, 5.2 million? Use a significance level of 0.05. Salary (millions of $) 108 14 5 8 5.1 4.3 7.8 2.5 Viewers (millions) Click the icon to view the critical values of the Pearson correlation coefficient r. What is the regression equation? y=+x (Round to three decimal places as needed.) X 1 1 5 8 5.7 8.2 10.9 4.4The percentage of the variation in the value of y this is explained by the lease squares regression line is Group of answer choices ρ the slope of the regression line. the correlation coefficient. the coefficient of determination. the y-intercept of the regression line. The data below shows the summary statistics for a regression analysis on car weight (in metric tons) and fuel consumption (in miles per gallon). b0=48.8b0=48.8 b1=−8.37b1=−8.37 r2=0.36r2=0.36 (Note that 0.362=0.13 and 0.36−−−−√=0.6)(Note that 0.362=0.13 and 0.36=0.6) Choose the correct interpretation of the y-intercept of the line:
- 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 63 inches. Is the result close to the actual weight of 522 pounds? Use a significance level of 0.05. Chest size (inches) 58 50 65 59 59 48 D 414 312 499 450 456 260 Weight (pounds) Click the icon to view the critical values of the Pearson correlation coefficient r. 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 63 inches? The best predicted weight for a bear with a chest size of 63 inches is pounds. (Round to one decimal place as needed.) Is the result close to the actual weight of 522 pounds? O A. This result is not very close to the actual weight of the bear. O B. This result is exactly the same as the actual weight of the bear. O C. This result is close to the actual weight of the…Hello tutor, please help me to understand this 2 part MCQ question. Thank you. Part A) Based on Image 1, A researcher examined the relationship between weight (y axis) and height (x axis) among 475 male subjects. He graphed the relationship in the scatter diagram below. Weight is measured in pounds, and height in inches. The equation of the regression line is y = 3.86*x – 110.42. Is it reasonable to presume that if a male is 107 inches tall, his weight will be 302.6 pounds? a) Yesb) No Part B) Based on Image 2, A researcher examined the relationship between Variables X and Y among 150 male subjects, and he graphed a scatter plot as seen below. The correlation coefficient for all the 150 data points is about 0.5. Let K be the correlation coefficient for the data points with X values lying between 130 to 150. Which of the following statements is correct?a) K is less than 0.50.b) K is more than 0.50.c) None of the other options.Consider the data. xi 2 6 9 13 20 yi 6 16 9 24 22 a. The estimated regression equation for these data is ŷ = 6.4 + 0.9x. What percentage of the total sum of squares can be accounted for by the estimated regression equation? (Round your answer to one decimal place.) b. What is the value of the sample correlation coefficient? (Round your answer to three decimal places.)
- Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. Height, x Stories, y 758 621 518 510 492 | 483 | 51 47 46 43 39 36 Find the regression equation. y = ☐ X+ (a) x = 503 feet (c) x = 802 feet (b) x = 649 feet (d) x = 728 feet (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.)Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heights (in feet) and the number of stories of six notable buildings in a city. 483 Height, x Stories, y 772 628 518 508 51 48 45 42 496 37 (a) x=499 feet (c) x=315 feet (b)x=639 feet (d) x = 732 feet 35 Find the regression equation. ŷ=x+ (Round the slope to three decimal places as needed. Round the y-intercept to two decimal places as needed.) Choose the correct graph below. O C. OB. O D. OA. Q Q ↓ 0 0 Height (feet) Height (feet) (a) Predict the value of y for x = 499. Choose the correct answer below. OA. 51 OB. 40 60+ 0- 800 60+ 0- 800 Q A 60- → 0 Height (feet) 800 60- 0- 800 0 Height (feet)Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (Each pair of variables has a significant correlation.) Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. The caloric content and the sodium content (in milligrams) for 6 beef hot dogs are shown in the table below. Calories, x Sodium, y 130 380 80 270 (a) x= 150 calories (c) x-120 calories 190 160 415 180 465 130 350 (b) X3D90 calories (d) x= 60 calories 540 (a) Predict the value of y for x= 150. Choose the correct answer below. O A. 212.451 B. 347.151 C. 414.501 O D. not meaningful (b) Predict the value of y for x= 90. Choose the correct answer below. O A. 212.451 O B. 347.151 es OC. 279.801
- Consider the data, 2 13 20 Yi 17 9 24 21 The estimated regression equation for these data is ŷ = 9 + 0.7x. What percentage of the total sum of squares can be accounted for by the estimated regression equation? (Round your answer to one decimal place.) % What is the value of the sample correlation coefficient? (Round your answer to three decimal places.)Using your favorite statistics software package, you generate a scatter plot with a regression equation and correlation coefficient. The regression equation is reported as y=85.73x+27.28 and the r=0.518.What proportion of the variation in y can be explained by the variation in the values of x?r² = __?__%Here is data with y as the response variable. a. Make a scatter plot of this data. Which point is an outlier? Enter as an ordered pair, e.g., (x,y). (x, y) b. Find the regression equation for the data set without the outlier. Enter the equation of the form mx + b rounded three decimal places. y wo X 48.4 77.3 88 67.1 108.3 75.9 64.8 -161.3 61.2 67.9 ŷw y 45.7 40.3 27.3 54.5 -63.2 36.3 73.2 96.5 82.2 119.8 = -- c. Find the regression equation for the data set with the outlier. Enter the equation of the form mx + b rounded to three decimal places.