Marina, Elena, Paloma, Alejandra and Rocío are 2, 3, 5, 7 and 8 years old and weigh 14, 20, 30, 42 and 44 kg respectively. With these data: (a) Find the equation of the regression line of age on weight. b) Estimate the approximate "weight" for a 6-year-old girl.
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Marina, Elena, Paloma, Alejandra and Rocío are 2, 3, 5, 7 and 8 years old and weigh 14, 20, 30, 42 and 44 kg respectively. With these data:
(a) Find the equation of the regression line of age on weight.
b) Estimate the approximate "weight" for a 6-year-old girl.

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- For nine months, Joan observes the average daily gas consumption for her house and the corresponding average temperature that month. She gets the following scatterplot (with regression line equation presented and drawn in): After collecting the data, Joan had insulation installed in her home. The next month, the average temperature was 30 and her home (with insulation) consumed 682 gas daily. Approximately how much gas did the insulation save her daily that month? a.)100 b.)150 c.)50 d.)200 Which of the terms does apply to the relationship between temperature and gas consumed? a.)linear b.)weak c.)perfect d.)positiveThe following data show the brand, price ($), and the overall score for six stereo headphones that were tested by Consumer Reports (Consumer Reports website). The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest). The estimated regression equation for these data is ŷ = 25.6590 +0.2934x, where x = price ($) and y = overall score. a. Compute SST, SSR, and SSE (to 3 decimals). SST = SSR = Brand Bose Scullcandy = Koss Phillips/O'Neill Denon JVC SSE = b. Compute the coefficient of determination 2 (to 3 decimals). 72 Price ($) 180 160 95 70 70 25 Score 75 71 62 56 40 26 h Comment on the goodness of fit. Hint: If 2 is greater than 0.70, the estimated regression equation provides a good fit. The least squares line - Select your answer a good fit as - Select your answer - proportion of the variability in y has been explained by the least squares line. c. What is the value of the sample correlation coefficient (to…Refer to the data in the table: x y -3 0 -2 0 -1 1 0 1 1 3 2 4 Part a: Make a scatter plot and determine which type of model best fits the data. Part b: Find the regression equation. Part c: Use the equation from Part b to determine y when x = 25.
- solve the last part, Compute the R2 for the regression.Lillian conducted a small survey of her friends and family. She asked them how many hours per week they spend reading digital documents (newspapers, blogs, books, etc.), and their age. She created the scatter plot below with the results she obtained. Draw the regression line that best represents this scatter plot and determine its equation.Please answer it with clean and complete solutions. Thank you.
- The following data show the brand, price ($), and the overall score for six stereo headphones that were tested by a certain magazine. The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest). The estimated regression equation for these data is ŷ = 21.656 + 0.333x, where x = price ($) and y = overall score. Brand Price ($) Score A 180 76 B 150 73 95 61 70 54 E 70 42 35 24 (a) Compute SST, SSR, and SSE. (Round your answers to three decimal places.) SST = SSR = SSE = (b) Compute the coefficient of determination r. (Round your answer to three decimal places.) 12 = Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) O The least squares line did not provide a good fit as a small proportion of the variability in y has been explained by the least squares line. O The least squares line provided a good fit as a small proportion of the variability in y…Use the time/tip data from the table below, which includes data from New York City taxi rides. (The distances are in miles, the times are in minutes, the fares are in dollars, and the tips are in dollars.) Find the regression equation, letting time be the predictor (x) variable. Find the best predicted tip for a ride that takes 22 minutes. How does the result compare to the actual tip amount of $5.05? Distance 1.80 8.51 1.40 1.65 12.71 1.02 1.32 Time Fare Tip 0.68 8.00 6.00 25.00 31.00 18.00 11.00 27.00 8.00 16.30 31.75 12.30 9.80 36.80 7.80 7.80 6.30 1.50 2.98 2.46 1.96 0.00 2.34 0.00 1.89 The regression equation is ŷ = + (x. (Round the y-intercept to two decimal places as needed. Round the slope to four decimal places as needed.)Refer to the data set:Part a: Make a scatter plot and determine which type of model best fits the data.Part b: Find the regression equation.Part c: Use the equation from Part b to determine y when x = 5.
- Part a: Make a scatter plot and determine which type of model best fits the data.Part b: Find the regression equation.Part c: Use the equation from Part b to determine y when x = 7.Use the time/tip data from the table below, which includes data from New York City taxi rides. (The distances are in miles, the times are in minutes, the fares are in dollars, and the tips are in dollars.) Find the regression equation, letting time be the predictor (x) variable. Find the best predicted tip for a ride that takes 30 minutes. How does the result compare to the actual tip amount of $4.70? Distance 1.80 1.40 12.71 1.32 8.51 0.49 2.47 Time 25.00 18.00 27.00 31.00 2.00 8.00 36.80 7.80 31.75 4.80 Fare 16.30 12.30 Tip 1.50 2.46 0.00 0.00 1.65 18.00 11.00 14.30 9.80 2.98 0.00 4.29 1.96 The regression equation is y = + X. (Round the y-intercept to two decimal places as needed. Round the slope to four decimal places as needed.)The following data show the brand, price ($), and the overall score for six stereo headphones that were tested by a certain magazine. The overall score is based on sound quality and effectiveness of ambient noise reduction. Scores range from 0 (lowest) to 100 (highest). The estimated regression equation for these data is ŷ = 23.462 + 0.315x, where x = price ($) and y = overall score. Brand Price ($) Score A 180 74 B 150 73 C 95 59 D 70 58 E 70 42 F 35 24 (a) Compute SST, SSR, and SSE. (Round your answers to three decimal places.) SST=SSR=SSE= (b) Compute the coefficient of determination r2. (Round your answer to three decimal places.) r2 = Comment on the goodness of fit. (For purposes of this exercise, consider a proportion large if it is at least 0.55.) The least squares line provided a good fit as a small proportion of the variability in y has been explained by the least squares line.The least squares line provided a good fit as a large proportion of…



