Find the least-squares line y= Bo + B,x that best fits the data (- 4,0), (- 1,0), (0,2), (1,5), and (4,5), assuming that the first and last data points are less reliable. Weight them half as much as the three interior points. The least-squares line is y=+ x. (Simplify your answers.)

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 Сoef SE Coef T P Constant 317.43 28.31 11.24 0.002 Elevation -31.272 3.511 -8.79 0.003 S = 11.8603 R-Sq = 96.2% 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 ý = a + bx. (a) Use the printout to write the least-squares equation. (b) For each 1000-foot increase in elevation, how many fewer frost-free days are…

Suppose the (X,Y) pairs are: (1,5), (2, 3), (3, 4), (4,2), (5,3), (6, 1). Would the least squares fit to these data be much different from the least squares fit to the same data with the first pair replaced by (1,15)? Briefly explain.

Consider the data points (2, 0), (3, 1), and (4, 5). Compute the least squares error for the given line. y = -4 + 2x Plot the points and the line. (Be sure to plot all points, even if they lie on the line.) No Solution 7 6 5 4 3 2 1 -4 -3 -2 -1 1 2 3 4 5 6 7 8 9 10 -1 -2 -3 -4 -5 -6 -7 Help Graph Layers Clear All Delete After you add an object to the graph you can use Graph Layers to view and edit its properties. Fill WebAssign. Graphing Tool

Percentages of public school students in fourth grade in 1996 and in eighth grade in 2000 who were at or above the proficient level in mathematics are given for eight western states. Find the equation of the least-squares line that summarizes the relationship between x = 1996 fourth-grade math proficiency percentage and y = 2000 eighth-grade math proficiency percentage. (Give the numerical values to four decimal places.) |4th grade 8th grade (1996) State (2000) Arizona 16 19 California 12 16 Hawaii 17 14 Montana 23 35 New Mexico 14 11 Oregon 22 30 Utah 24 24 Wyoming 20 23 n USE SALT ŷ =

In the least-squares line  = 5 – 9x, what is the value of the slope?When x changes by 1 unit, by how much does y change? When x increases by 1 unit, y decreases by 9 units. When x decreases by 1 unit, y decreases by 9 units.     When x increases by 1 unit, y decreases by −9 units. When x increases by 1 unit, y increases by 9 units.

The height (sidewalk to roof) of notable tall buildings in America is compared to the number of stories of the building (beginning at street level). Stories (x) Height (y) 56 1050 29 428 26 362 40 529 60 790 22 401 38 380 110 1454 100 1127 46 700 Calculate the least squares line. Put the equation in the form of:  ŷ = a + bx.  (Round your answers to three decimal places.)ŷ =  +  x

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 316.08 28.31 11.24 0.002 Elevation -31.974 3.511 -8.79 0.003 S = 11.8603 R-Sq = 97.8%       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 =  316.08 +-31.974x For each 1000-foot increase in…

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…