Independent Dependent Variable Variable 15 5 12 7 10 7 11 What is he least squares regression estimate of the intercept? a) -1.3 O b) 16.41176 c) 21.4 -7.647
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- The following fictitious table shows kryptonite price, in dollar per gram, t years after 2006. t= Years since 2006 0 1 2 3 4 5 6 7 8 9 10 K= Price 56 51 50 55 58 52 45 43 44 48 51 Make a quartic model of these data. Round the regression parameters to two decimal places.The following table lists the birth weights (in pounds), x, and the lengths (in inches), y, for a set of newborn babies at a local hospital. Birth Weights and Lengths Birth Weight (in Pounds), x 1212 1010 88 1111 1111 33 55 44 77 66 Length (in Inches), y 2121 2020 1717 2222 2222 1616 1717 1616 1919 1919 Copy Data Step 1 of 2 : Find an equation of the least-squares regression line. Round your answer to three decimal places, if necessary.To study the tensile strength of a certain type of wire, the following pairs of observations were recorded, wherex is the diameter in cm and y is the mass supported in kg/cm.x: 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 2.4y: 14 26 50 56 42 98 82 88 134 124 Calculate the least-squares regression line and extrapolate the regression line to a diameter of 0.2 cm. Alsoexplain your result.
- The following data is given: x -7 -4 -1 0 2 5 7 y 20 14 5 3 -2 -10 -15 Use linear least-squares regression to determine the coefficients m and b in the function y=mx+b that best fit the data.The table contains data on vehicle speed (h) and fuel consumption (lt / 100km) of 5 randomly selected vehicles. Estimate the average fuel consumption of a vehicle traveling at 45 km / h using the simple linear regression equation between vehicle speed and fuel consumption. Speed 55 60 65 70 75 Consumption 13 12 11 10 9 a. 15 b. 8 c. 7 d. 20A security firm wants to renew the uniforms used by his personnel. It starts by collecting data on their height and weight. The following data was collected from the 19 employees Height (cm) Weight (kg) 168 72 175 88 167 84 171 87 161 67 164 55 177 82 170 60 167 60 184 77 183 98 163 53 186 77 165 64 173 89 161 65 179 77 169 64 174 87 a). Construct an equation to relate these variables, using the least-squares method to determine the regression coefficients, b0 and b1. b). Interpret the meaning of b0 and b1 in this problem. c) determine the coefficient of determination, r2 and interpret its meaning.
- Two specimens of cold rolled steel sheet, which have differentcopper contents and annealing temperature are measured in hardness with the following results: First column = HardnessSecond column = Copper contentThird column = Annealing temperature a) Create a scatter plot to verify that it is reasonable to assume that the regression of Y on x is linear. b) Fit a straight line using the method of least squares. c) Fit an equation of the form (image 2), where x1 represents the copper content, x2 represents the annealing temperature, and y represents the hardness.The following data represent the number of flash drives sold per day at a local computer shop andtheir prices.Price (x) Units Sold (y)$34 336 432 635 530 938 240 1 a. Develop a least squares regression line and explain what the slope of the line indicates.b. Compute the coefficient of determination and comment on the strength of relationship betweenx and y.Listed below are the overhead widths (cm) of seals measured from photographs and the weights (kg) of the seals. Overhead width 7.2 7.4 9.8 9.4 8.8 8.4 Weight 116 154 245 202 200 191 The four pairs of values below were obtained from the regression equation. Which is an extrapolation? a) overhead width 7.5 cm, weight 144 kg b) overhead width 10 cm, weight 245 kg c) overhead width 7.2 cm, weight 132 kg d) overhead width 8.1 cm, weight 169 kg
- The table contains data on vehicle speed (h) and fuel consumption (lt / 100km) of 5 randomly selected vehicles. Estimate the average fuel consumption of a vehicle traveling at 45 km / h using the simple linear regression equation between vehicle speed and fuel consumption. Speed 55 60 65 70 75 Consumption 11 10 9 8 7 Please choose one: a. 6 b. 5 c. 13 D. 8The following data was collected by a particular company to determine if a relationship between the number of people in a household and weekly food expenditures exists. Regression analysis is done using this data, and the following Excel see attached image Household Number in Household Weekly Food Expenses 1 2 $95 2 3 $137 3 5 $165 4 2 $105 5 4 $227 6 4 $240 7 5 $185 a. Using the least-squares regression line (from the excel output the regression equation is y=51.779 + 31.662x) , estimate the weekly food expenses for a household that has 10 people. b. Briefly describe any concerns that you may have with your forecast or extrapolation in question above. c. Give examples of two variables that should be included in the model above, explaining why these would make the model a better fit.