Answer:
(a) MAE = 5.20
(b) MSE = 10
(c) MAPE = 38.60%
(d) Forecast for week 7 = 14
Step-by-step explanation:
Note: See the attached excel for the calculations of the Error, Error^2, and Error %.
(a) mean absolute error
MAE = Total of absolute value of error / Number of observations considered = |Error| / 5 = 26 / 5 = 5.20
(b) mean squared error
MSE = Total of Error^2 / Number of observations considered = Error^2 / 5 = 150 / 5 = 10
(c) mean absolute percentage error (Round your answer to two decimal places.)
MAPE = Total of Error % / Number of observations considered = Error % / 5 = 193.02 / 5 = 38.60%
(d) What is the forecast for week 7?
Since the forecast is based on the naive method (most recent value), the forecast for week 7 is value for week 6. Therefore, we have:
Forecast for week 7 = 14
Answer:
a. 96 square units
Step-by-step explanation:
The figure is a rectangle with width AB = (20-12) = 8 units and height BC = (20-8) = 12 units.
The area of the rectangle is (8 units)×(12 units) = 96 square units.
Suppose you performed a regression analysis. The mse for this scenario is 0.105
Regression is a statistical method used in finance, making an investment, and different disciplines that attempt to determine the electricity and man or woman of the relationship between one established variable (commonly denoted through Y) and a sequence of different variables (called independent variables).
We are able to say that age and peak can be described through the usage of a linear regression version. because someone's peak will increase as age will increase, they have got a linear courting. Regression fashions are commonly used as statistical proof of claims regarding regular statistics.
"Regression" comes from "regress" which in turn comes from Latin "regresses" - to head returned (to something). In that feel, regression is the approach that permits "to head again" from messy, hard-to-interpret data, to a clearer and more significant version.
y ypred (y-ypred)^2
1 1.1 0.01
1.5 1.3 0.04
2.8 3.2 0.16
3.7 3.7 0
The error sum of the square is given by
ESS = (y- )
ESS=0.21
The mean square error is given by
ESS MSE = ESS/dfe
MSE = \frac{0.21}{2}
MSE = 0.105
Learn more about regression here brainly.com/question/26755306
#SPJ4
Answer:
you have all of them right just make sure for number six you have 1/3125. you have all the work im not sure what i should solve.
Subtract 7 from both sides then divide both sides by X so the correct answer would be B.) y= n-7/x
