Different hotels in a certain area are randomly selected, and their ratings and prices were obtained online. Using technology, with x representing the ratings and y representing price, we find that the regression equation has a slope of 130 and a y-intercept of - 370. Complete parts (a) and (b) below. OA.y=+x OB.y=+x OC. y=+x
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- The table shows the average weekly wages (in dollars) for state government employees and federal government employees for 8 years. The equation of the regression line is y=1.410x−17.174. Complete parts (a) and(b) below.The relationship between number of TikToks watched while studying and average grade on an exam is defined by the following linear regression equation: Y=-0.3X+70 Interpret the equation by answering the following: a. What is the slope? b. What does the slope tell us in this example?The linear regression equation for the data from the number 2 is y=.27x+5.82. Describe the slope of the linear best-fit equations.
- In regression equation alpha is called as а. Al O b. Dependent variable c. Slope d. InterceptHeight Weight GPA Study TV Computer FamilySz Floors stairs friends female Acctg Mgmt Mktg Fin IntBus Other 67 138 4 6 2 1. 2 26 6. 1 73 175 3.47 5 4 26 1 62 112 4 6 2 1. 4 34 3 1 1. 64.5 122 3.5 3.4 1. 3 47 4 1 1. 69 135 4 4 2 4 13 1. 61 129 3.8 4 2 3 5 17 1. 1. 64 135 3.4 3 2 5 1. 1 1. 68 150 4 10 1 4 2 31 4 1 1 70 130 3.8 4 1 2 4 2 26 8. 1 65 172 3.6 2.5 1.5 0.5 4 2 26 8. 1 74 235 2.6 1. 1. 1. 4 3 52 1. 69 150 3 2 3 3 4 3 26 1. 72 152 2.8 2.5 0.5 3 5 3 30 10 1. 73 155 3 1. 2 4 2 26 1 74 170 3.75 1.5 1.5 2 15 5 1. 68 150 3 2.5 1. 4 3 26 10 1 63 115 2.5 3 2.5 3 2 13 8 1. 1 71 180 2.1 1 3 3 4 13 10 1 72 167 2.7 2. 4 4 2 18 3 72 180 3.8 2 1.5 0.5 1. 300 68.575 152.6 3.341 3.395 1.55 1.75 4.1 2.2 38.25 5.8 s= 4.146257 28.65842 0.584798 2.137257 0.759155 1.409554 0.640723 0.695852 62.7215 2.587419 ------ ---- ----- ----- ----- ----- ---- ----- ----- ----- ----- ------ ----- ---- ---- --A sports-equipment researcher was interested in the relationship between the speed of a golf club (in feet per second) and the distance a golf ball travels (in yards). Information was collected on several golfers and was used to obtain the regression equation ŷ = 2x - 106, where x represents the club speed and ŷ is the predicted distance. Which statement best describes the meaning of the slope of the regression line? For each increase in distance by 1 yard, the predicted club speed increases by 2 ft/sec. For each increase in distance by 1 yard, the predicted club speed decreases by 106 ft/sec. For each increase in club speed by 1 ft/sec, the predicted distance increases by 2 yards. For each increase in club speed by 1 ft/sec, the predicted distance decreases by 106 yards.
- Find the regression equation, letting the first variable be the predictor (x) variable. Find the best predicted Nobel Laureate rate for a country that has 78.5 Internet users per 100 people. How does it compare to the country's actual Nobel Laureate rate of 1.9 per 10 million people? Click the icon to view the data. Data table Find the equation of the regression line. Internet Users Per 100 Nobel Laureates V = + (Round the constant to one decimal place as needed. Round the coefficient to three decimal places as needed.) 79 5.4 79.6 24.5 78.7 8.5 44.7 0.1 83.6 6.1 38.6 0.1 90.2 25.5 89.4 7.7 79.1 9. 83.1 12.8 52.7 1.9 76.8 12.7 57.1 3.3 79.8 1.5 92.3 11.5 93.8 25.7 64.7 3.1 58.2 1.9 67.3 1.7 94 31.8 84.5 31.3 87 18.9 77.1 10.7Using data from the attatched chart, and the equation stated below, answer questions a,b,and c. linear equation: y=0.078x+2.42 a. Write a linear equation in slope-intercept form that models the data. b. Use the equation from part (a) to project the demand for teachers in 2024. c. Project the year when the demand for teachers will reach 6 million.Using the weights (lb) and highway fuel consumption amounts (mi/gal) of the 48 cars listed in the accompanying data set, one gets this regression equation: y = 58.9-0.00749x, where x represents weight. Complete parts (a) through (d). Click the icon to view the car data. The site to your captio V.UVITU. D. The slope is -0.00749 and the y-intercept is 58.9. c. What is the predictor variable? ... OA. The predictor variable is highway fuel consumption, which is represented by x. OB. The predictor variable is highway fuel consumption, which is represented by y. C. The predictor variable is weight, which is represented by x. OD. The predictor variable is weight, which is represented by y. d. Assuming that there is a significant linear correlation between weight and highway fuel consumption, what is the best predicted value for a car that weighs 2994 lb? The best predicted value of highway fuel consumption of a car that weighs 2994 lb is (Round to one decimal place as needed.) mi/gal.
- The table shows the amounts of crude oil (in thousands of barrels per day) produced by a certain country and the amounts of crude oil (in thousands of barrels per day) imported by the same country for seven years. The equation of the regression line is y = - 1.269x + 16,635.60. Complete parts (a) and (b) below. Produced, x Imported, y 5,718 5,612 5,409 5,228 5,128 5,006 O 9,106 9,631 10,000 10,140 10,133 10,059 5,759 9,318 (a) Find the coefficient of determination and interpret the result. (Round to three decimal places as needed.)Using the weights (Ib) and highway fuel consumption amounts (mi/gal) of the 48 cars listed in the accompanying data set, one gets this regression equation: y = 58 9-0.00749x, where x represents weight Complete parts (a) through (d). Click the icon to view the car data. 東 b. What are the specific values of the slope and y-intercept of the regression line? O A. The slope is 58.9 and the y-intercept is 0.007499. B. The slope is -0.00749 and the y-intercept is 58.9. O C. The slope is 58.9 and the y-intercept is -0.00749. O D. The slope is 0.00749 and the y-intercept is 58.9. c. What is the predictor variable? O A. The predictor variable is highway fuel consumption, which is represented by x. B. The predictor variable is weight, which is represented by x. O C. The predictor variable is weight, which is represented by y O D. The predictor variable is highway fuel consumption, which is represented by y. d. Assuming that there is a significant linear correlation between weight and highway fuel…A teacher wants to form a linear regression equation to predict a student's Score on the final based on the number of hours they spent studying for it. Final scores are in percents. y=2x + 60 R-Squared = 0.65 %3D What does the slope mean in terms of the situation? O For each additional hour a student studies, their grade on the final increases by 2%. O For each additional 2 hours a student student studies, their score on the final increases by 1%. O Every hour a student studies, increases their score on the final. O Always choose C. O The more a student studies, the better they will do on the final.