Respuesta :
Answer: Y = $11.25X + $ 15640
Explanation:
1) This is the information given:
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
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
Explanation:
1) This is the information given:
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
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
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
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