An agricultural scientist planted alfalfa on several plots of land, identical except for the soil pH.  Following are the dry matter yields (in pounds per acre) for each plot.   pH 4.6 4.8 5.2 5.4 5.6 5.8 6 Yield 1056 1833 1629 1852 1783 2647 2181     Compute the least-squares line for predicting yield from pH. Round the answers to two decimal places.

Round to two decimal places as needed.

Use the data provided on Canvas. In automotive assembly processes, automation cannot always guarantee the dimensional accuracy of a car assembly as required by the design specification. Thus, some skillful workers will visually inspect those assembled car bodies and conduct manual adjustments when necessary. These workers are called "Fitter" in the automotive industry. This scenario is illustrated in the following figure. Automatic assembly process X P₁ Fitter Y P₂ One critical quality characteristics on a car assembly were measured at both P₁ (before fitter) and P₂ (after fitter). The data are labeled as X and Y, respectively, and 20 measurements are shown below. Please use the risk adjustment method to test if X and/or Y are in control. Please show X chart, Y chart and Z chart.

The following data is given: x -2 -1 0 1 2 y 1.5 3.2 4.5 3.4 2 Determine the coefficients a and b in the function y=a/(x2+b) that best fit the data. (Write the function in a linear form, and use linear least-squares regression to determine the value of the coefficients.) Once the coefficients are determined make a plot that shows the function and the data points.

When a stone is dropped in a pond, ripples are formed and travel in concentric circles away from where the stone was dropped. The equation of the least-squares regression line is log(Area) = 0.490 + 2.004 log(Time). WWhat is the predicted area of the circle, in cm2, 4 seconds after the stone is dropped? O 49.72 cm2 O 199.43 cm2 O 311.89 cm? O 1854.10 cm2

The horsepower (Y, in bhp) of a motor car engine was measured at a chosen set of values of running speed (X, in rpm). The data are given below (the first row is the running speed in rpm and the second row is the horsepower in bhp): rpm 1100 1400 1700 2300 2700 3200 3500 4000 4600 5200 5600 6100 Horsepower (bhp) 50.2 64.29 67.83 98.56 131.09 163.65 161.55 198.62 226.03 254.71 283.63 299.81 The mean and sum of squares of the rpm are 3450.0000 rpm and 173900000.0000 rpm 22 respectively; the mean of the horsepower values is 166.6642 bhp and the sum of the products of the two variables is 8506152.0000 rpm bhp.    Given Values: a) Slope: 0.052 b) Intercept: -11.694 c) 95% Confidence Interval when the standard error of the estimate of the slope coefficient was found to be 0.001160: (0.0494, 0.0546) please answer the following: Part e)Without extending beyond the existing range of speed values or changing the number of observations, we would expect that increasing the variance of the…