Choosing Models. For the
Linear,
Quadratic,
Quadratic,
Polynomial, neither quadratic nor linear.
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Intermediate Algebra (13th Edition)
- regression is done on data that represent ordered pairs true or falsearrow_forwardYou are part of a government task force evaluating whether new models of cars will meet fuel efficiency standards set out by the newly signed climate bill. You have run an ANCOVA model that predicts fuel efficiency (in miles per gallon) as a function of vehicle weight (measured in thousands of lbs, where a value of 2.5 would correspond to 2,500 lbs), horsepower, and number of cylinders in the car (cylinders is a factor in this model with 3 levels: 4 cylinders, 6 cylinders, and 8 cylinders). Your analysis tells you the following; The mean miles per gallon of all cars analyzed is 20.09 The mean weight of all cars analyzed is 3.217 thousand lbs The mean horsepower of all cars analyzed is 146.7 The regression coefficient for weight is -3.18 miles per gallon per additional thousand lbs The regression coefficient for horsepower is -0.023 miles per gallon per additional unit of horsepower Cars with 4 cylinders get 2.13 more miles per gallon, on average, than the average car Toyota is…arrow_forwardSolve the problem. The data in the table represent the amount of raw material (in tons) put into an injection molding machine each day (x), and the amount of scrap plastic (in tons) that is collected from the machine every four weeks (y). Also shown below are the outputs from two different statistical technologies (TI-83/84 Calculator and Excel). A scatterplot of the data confirms that there is a linear association. Report the equation for predicting scrap from raw material using words such as scrap, not x and y. State the slope and intercept of the prediction equation. Round all calculations to the nearest hundredth. X y 2.71 3.61 2.33 2.80 2.33 2.77 2.21 2.34 2.11 2.15 2.08 2.06 1.98 1.95 1.84 1.84 2.02 1.95 1.73 1.68 LinReg y=a+bx a = -2.376991175 b=2.192699333 r² =.9806834986 P = .9902946524 Intercept X Variable 1 Coefficients -2.376991175 2.192699333 scrap = 2.19 -2.38(raw material); slope = 2.19 and the intercept is -2.38., scrap = -2.38 + 2.19(raw material); slope = -2.38 and…arrow_forward
- Toesdon 3: The U.S. Bureau of the Census predicted that the population of Florida would be about 16.4 million in 2010 and then would increase by about 0.35 million per year until 2015. Write a linear 201er that predicts the population, y, of Florida (in millions) in terms of x, the number of years since 2010. wurla Jaum uoY sod o no 2odunlo eniwollot orli storw Tedos A:l noltesuD vdw nisloxaarrow_forwardDerive the linear interpolant through the two data points (1.0, 2.0) and (1.1, 2.5).Then, derive the quadratic interpolant through these two points and the point (1.2, 1.5). Show a graphdepicting this situation.arrow_forwardSuppose that the number of tee shirts sold (N) depends linearly on the price charged (x). Write an equation showing this dependence.arrow_forward
- Regression will show a in a broader sense. O a. Functional relationship O b. Partial relationship Oc. Impartial relationship O d. Managerial relationshiparrow_forwardWhere is the quadratic model for the data?arrow_forwardThe electric power consumed each month by a chemical plant is thought to be related to the average ambient temperature (x₁), the number of days in the month (x₂), the average product purity (x3), and the tons of product produced (x4). The past year's historical data are available and are presented in the following table: Y 240 236 270 274 301 316 270 296 267 276 288 261 25 31 45 60 65 72 80 84 75 60 50 38 X2 24 21 24 25 25 26 25 25 24 25 25 23 Fit a multiple linear regression to predict power (y) using x1, X2 X3, and X4. Calculate R2 for this model. Round your answer to 3 decimal places. 91 90 88 87 91 94 87 86 88 91 90 89 X4 100 95 110 88 94 99 97 96 110 105 100 98arrow_forward
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