Show that the least squares line y=B, +B,x will always pass through the point (x,5). 5.
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- For a sample of 15 trees, the volume of lumber (y) (in cubic meters) and the diameter (x) (in centimeters) at a fixed height above ground level was measured. The following summary statistics were obtained: x̄ = 35.2 sx = 8.9 ȳ = 0.78 sy = 0.48 r = 0.95 a) Compute the least-squares regression line for predicting volume from diameter. B)Predict the volume for a tree whose diameter is 42 centimetersFor the past decade, rubber powder has been used in asphalt cement to improve performance. An article includes a regression of y = axial strength (MPa) on x = cube strength (MPa) based on the following sample data: x 112.3 97.0 92.7 86.0 102.0 99.2 95.8 103.5 89.0 86.7 y 75.4 71.3 58.1 48.5 74.1 73.7 67.7 59.5 58.0 48.6 (a) Obtain the equation of the least squares line. (Round all numerical values to four decimal places.)y = Interpret the slope. A one MPa increase in axial strength is associated with an increase in the predicted cube strength equal to the slope.A one MPa decrease in cube strength is associated with an increase in the predicted axial strength equal to the slope. A one MPa increase in cube strength is associated with an increase in the predicted axial strength equal to the slope.A one MPa decrease in axial strength is associated with an increase in the predicted cube strength equal to the slope. (b) Calculate the coefficient of determination.…while using the t-test to test whether regression is significant, in the model yi=β0+β1xi+εiyi=β0+β1xi+εi, what is the calculated student-t statistics (H0:β1=0H0:β1=0 versus H1:β1≠0H1:β1≠0). Calculate the least squares estimates of β0β0 in the model yi=β0+β1xi+εi Calculate the sum of squares of y denoted by Syy , the sum of squares of x denoted by Sxx and sum of squares (products) of x and y denoted by Sxy while using analysis of variance (ANOVA) to test whether regression is significant, in the model yi=β0+β1xi+εiyi=β0+β1xi+εi, what is the residual or error sum of squares due to regression, SSE. kindly help with this question
- For the past decade, rubber powder has been used in asphalt cement to improve performance. An article includes a regression of y = axial strength (MPa) on x = cube strength (MPa) based on the following sample data: x 112.3 97.0 92.7 86.0 102.0 99.2 95.8 103.5 89.0 86.7 y 74.6 71.1 57.5 48.4 74.0 72.9 68.3 59.8 57.6 48.0 (a) Obtain the equation of the least squares line. (Round all numerical values to four decimal places.)y = −32.6485+0.9943x Interpret the slope. A one MPa increase in axial strength is associated with an increase in the predicted cube strength equal to the slope.A one MPa decrease in cube strength is associated with an increase in the predicted axial strength equal to the slope. A one MPa decrease in axial strength is associated with an increase in the predicted cube strength equal to the slope.A one MPa increase in cube strength is associated with an increase in the predicted axial strength equal to the slope. (b) Calculate the coefficient of…The peanut crop was harvested from five fields of various area. The following data are the mass of the crop from each field y (in kilograms) and the field area x (in hectares). y 7360 15760 13690 20080 12910 x 2.34 3.92 3.35 4.56 2.56 Round your intermediate answers to four decimal places (e.g. 98.7654).(a) Fit the simple linear regression model using the method of least squares. Find the estimate of σ2.Round your answer to the nearest integer (e.g. 9876).σ^2= (b) What change in the mean mass is expected when the field area changes by 1 hectare?Round your answer to the nearest integer (e.g. 9876).β^1= (c) Calculate the fitted value of y corresponding to x=3.92. Find the corresponding residual.Round your answer to the nearest integer (e.g. 9876).y^= Round your answer to the nearest integer (e.g. 9876).e= (d) Estimate the mean mass of the crop harvested from 4.5 hectares.Round your answer to the nearest integer (e.g. 9876).y^=An owner of a home in the Midwest installed solar panels to reduce heating costs. After installing the solar panels, he measured the amount of natural gas use y (in cubic feet) to heat the home and outside temperature x (in degree-days, where a day’s degree-days are the number of degrees its average temperature falls below 65F) over a 23-month period. He then computed the least squares regression line for predicting y from x and found it to be, ŷ=85+16x How much, on average, does gas used increase for each additional degree-day? The predicted amount of gas used when the outside temperature is 20 degree- days.
- Compute the least-squares regression line for predicting y from x given the following summary statistics. Round the slope and y-intercept to at least four decimal places. x = 12.5 sx = 2.2 y = 1400 sy = 1.8 r = 0.50 Regression line equation: y^ = ___. image attached bellow for better view.The following data show the number of class sessions missed during a semester of SOC221 and the final grade for a sample of 8 students selected at random. Number of Sessions Missed Final Grade (x) (y) 0 96 2 88 12 68 6 91 8…(a) Find the equation of the least-squares line for the data. (Round all numerical values to two decimal places.) y= ?
- An owner of a home in the Midwest installed solar panels to reduce heating costs. After installing the solar panels, he measured the amount of natural gas used y (in cubic feet) to heat the home and outside temperature x (in degree-days, where a day's degree-days are the number of degrees its average temperature falls below 65° F) over a 23-month period. He then computed the least-squares regression line for predicting y from x and found it to be ŷ = 85 + 16x. The software used to compute the least-squares regression line for the equation above says that r2 = 0.98. This suggests which of the following? 1. Gas used increases by square root of 0.98 = 0.99 cubic feet for each additional degree-day? 2. Although degree-days and gas used are correlated, degree-days do not predict gas used very accurately. 3. Prediction of gas used from degree-days will be quite accurate.Fit a curve of the form g(x) = Ax-1 to the dataset using the Least Squares Method. Calculate the corrected values and the total squared error.You are conducting a test of independence for the claim that there is an association between the row variable and the column variable. X Y Z A 20 23 32 B 20 30 28 What is the chi-square test-statistic for this data?χ2=Report all answers accurate to three decimal places.