The h.w. grant corporation used regression analysis to predict the annual cost of indirect materials. the results were as follo
ws: indirect materials cost explained by units produced constant $15,640 standard error of y estimate $3,600 r2 0.7704 number of observations 22 x coefficient(s) 11.25 standard error of coefficient(s) 2.19 what is the cost estimation equation?
Indirect material cost: y explained by units produced: x Linear regression. Cost estimation equation: y=mx+b Constant: b=$15,640 Standard error of y estimate=$3,600 r^2=0.7704 Number of observations: n=22 x coeffient: m=11.25 Standard error of x coefficient=2.19
m=11.25, b=15,640 → y=11.25x+15,640
Answer: The cost estimation equation is y=11.25x+15,640
<span>Indirect
materials cost explained by units produced
Constant: $15,640 Standard
error of y estimate $3,600 r2 0.7704 Number of observations 22 X-coefficient(s) 11.25 Standard error of coefficient(s) 2.19
2) The regresssion analysis permits to obtain a linear equation to represent the correlation between two variables and predict one in terms of the other.
The form of the equation is that of a linear function:
Y = AX + B
3) So, the cost estimation requested is the varibale times its coefficient plus the constant.
Given: X-coefficient = 11.25 constant = $ 15,640
Equation:Y = $11.25X + $ 15640 </span> The other inforamation, i.e. standard error of Y estimate, r^2, number of observations, and standard error coefficientes are other statistical numbers that permit to understand the quality of the regression
You first need to break each shape down. for example in the top right corner you have a pyramid and a triangular prism. find the area for those two shapes and add them together and you will have the surface area for the entire shape