The position of a particle x(t) on an axis has been monitored. The results are shown in the following table. By the least squares method, fit the data to a quadratic model: Report the position predicted by the model for t = 10.
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The position of a particle x(t) on an axis has been monitored. The results are shown in the following table.
By the least squares method, fit the data to a quadratic model:
Report the position predicted by the model for t = 10.
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- A researcher wishes to examine the relationship between years of schooling completed and the number of pregnancies in young women. Her research discovers a linear relationship, and the least squares line is: ŷ = 2 – 3xwhere x is the number of years of schooling completed and y is the number of pregnancies. The slope of the regression line can be interpreted in the following way: %3D O When amount of schooling increases by one year, the number of pregnancies decreases by 2. O When amount of schooling increases by one year, the number of pregnancies increases by 2. O When amount of schooling increases by one year, the number of pregnancies decreases by 3. O When amount of schooling increases by one year, the number of pregnancies increases by 3.A researcher wishes to examine the relationship between years of schooling completed and the number of pregnancies in young women. Her research discovers a linear relationship, and the least squares line is: ŷ = 25x where x is the number of years of schooling completed and y is the number of pregnancies. The slope of the regression line can be interpreted in the following way: When amount of schooling increases by one year, the number of pregnancies tends to increase by 5. When amount of schooling increases by one year, the number of pregnancies tends to decrease by 5. When amount of schooling increases by one year, the number of pregnancies tends to increase by 2. When amount of schooling increases by one year, the number of pregnancies tends to decrease by 2.The following data are the average annual repair cost (in O.R.) and the age of automobiles ( in years). Car age (x) 1 2 3 4 5 Repair Cost (y) 100 150 320 350 380 Find the equation of Y on X by least-squares regression method.
- A researcher wishes to examine the relationship between years of schooling completed and the number of pregnancies in young women. Her research discovers a linear relationship, and the least squares line is: ŷ = 1 - 5xwhere x is the number of years of schooling completed and y is the number of pregnancies. The slope of the regression line can be interpreted in the following way: O When amount of schooling increases by one year, the number of pregnancies increases by 1. When amount of schooling increases by one year, the number of pregnancies decreases by 1. When amount of schooling increases by one year, the number of pregnancies decreases by 5. When amount of schooling increases by one year, the number of pregnancies increases by 5.A researcher wishes to examine the relationship between years of schooling completed and the number of pregnancies in young women. Her research discovers a linear relationship, and the least squares line is: ŷ = 1 – 2xwhere x is the number of years of schooling completed and y is the number of pregnancies. The slope of the regression line can be interpreted in the following way: O When amount of schooling increases by one year, the number of pregnancies increases by 2. O When amount of schooling increases by one year, the number of pregnancies decreases by 1. O When amount of schooling increases by one year, the number of pregnancies increases by 1. O When amount of schooling increases by one year, the number of pregnancies decreases by 2. Check AnswerA researcher wishes to examine the relationship between years of schooling completed and the number of pregnancies in young women. Her research discovers a linear relationship, and the least squares line is: i = 2 – 5z where x is the number of years of schooling completed and y is the number of pregnancies. The slope of the regression line can be interpreted in the following way: O When amount of schooling increases by one year, the number of pregnancies tends to decrease by 5. O When amount of schooling increases by one year, the number of pregnancies tends to increase by 5. O When amount of schooling increases by one year, the number of pregnancies tends to decrease by ns 2. O When amount of schooling increases by one year, the number of pregnancies tends to increase by 2. urse Submit Question math.com/assess2/3/skip/10 here to search R
- We use the form ŷ = a + bx for the least-squares line. In some computer printouts, the least-squares equation is not given directly. Instead, the value of the constant a is given, and the coefficient b of the explanatory or predictor variable is displayed. Sometimes a is referred to as the constant, and sometimes as the intercept. Data from a report showed the following relationship between elevation (in thousands of feet) and average number of frost-free days per year in a state. A Minitab printout provides the following information. Predictor Coef SE Coef T P Constant 315.27 28.31 11.24 0.002 Elevation -31.812 3.511 -8.79 0.003 S = 11.8603 R-Sq = 96.8% Notice that "Elevation" is listed under "Predictor." This means that elevation is the explanatory variable x. Its coefficient is the slope b. "Constant" refers to a in the equation ŷ = a + bx. (a) Use the printout to write the least-squares equation. ŷ = + x (b) For each 1000-foot increase in elevation,…We use the form ŷ = a + bx for the least-squares line. In some computer printouts, the least-squares equation is not given directly. Instead, the value of the constant a is given, and the coefficient b of the explanatory or predictor variable is displayed. Sometimes a is referred to as the constant, and sometimes as the intercept. Data from a report showed the following relationship between elevation (in thousands of feet) and average number of frost-free days per year in a state. A Minitab printout provides the following information. Predictor Coef SE Coef T P Constant 316.62 28.31 11.24 0.002 Elevation -30.516 3.511 -8.79 0.003 S = 11.8603 R-Sq = 96.2% The printout gives the value of the coefficient of determination r2. What is the value of r? Be sure to give the correct sign for r based on the sign of b. (Round your answer to four decimal places.) What percentage of the variation in y can be explained by the corresponding variation in x and the least-squares…The following table shows the length, in centimeters, of the humerus and the total wingspan, in centimeters, of several pterosaurs, which are extinct flying reptiles. (A graphing calculator is recommended.) (a) Find the equation of the least-squares regression line for the data. (Where × is the independent variable.) Round constants to the nearest hundredth. y= ? (b) Use the equation from part (a) to determine, to the nearest centimeter, the projected wingspan of a pterosaur if its humerus is 52 centimeters. ? cm
- The following data are provided: 1 2 3 5 y 2.2 2.8 3.6 4.5 5.5 You want to use least-squares regression to fit this data with the following model, b y = 1+ ax +- Determine the coefficients a, & b. 4-Biologist Theodore Garland, Jr. studied the relationship between running speeds and morphology of 49 species of cursorial mammals (mammals adapted to or specialized for running). One of the relationships he investigated was maximal sprint speed in kilometers per hour and the ratio of metatarsal-to-femur length. A least-squares regression on the data he collected produces the equation ŷ = 37.67 + 33.18x %3D where x is metatarsal-to-femur ratio and ŷ is predicted maximal sprint speed in kilometers per hour. The standard error of the intercept is 5.69 and the standard error of the slope is 7.94. Construct an 80% confidence interval for the slope of the population regression line. Give your answers precise to at least two decimal places. Lower limit: Upper limit:A researcher wishes to examine the relationship between years of schooling completed and the number of pregnancies in young women. Her research discovers a linear relationship, and the least squares line is: ý = 2-5z where x is the number of years of schooling completed and y is the number of pregnancies. The slope of the regression line can be interpreted in the following way: O When amount of schooling increases by one year, the number of pregnancies tends to decrease by 5. O When amount of schooling increases by one year, the number of pregnancies tends to increase by 5. ns O When amount of schooling increases by one year, the number of pregnancies tends to decrease by 2. re O When amount of schooling increases by one year, the number of pregnancies tends to increase by 2. urse Submit Question here to search 立