Consider the following time series data. Week123456Value191415101715 Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy. Mean absolute error. If required, round your answer to one decimal place.fill in the blank 1Mean squared error. If required, round your answer to one decimal place.fill in the blank 2Mean absolute percentage error. If required, round your intermediate calculations and final answer to two decimal places.fill in the blank 3%What is the forecast for week 7? If required, round your answer to two decimal place.

The question is about forecastingGiven :To find :1 ) Mean absolute error2 ) Mean squared error3 )…

Answered: onsider the following time series data.…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Question

Consider the following time series data.

Week	1	2	3	4	5	6
Value	19	14	15	10	17	15

Using the naïve method (most recent value) as the forecast for the next week, compute the following measures of forecast accuracy.

Mean absolute error. If required, round your answer to one decimal place.

fill in the blank 1
Mean squared error. If required, round your answer to one decimal place.

fill in the blank 2
Mean absolute percentage error. If required, round your intermediate calculations and final answer to two decimal places.

fill in the blank 3%
What is the forecast for week 7? If required, round your answer to two decimal place.

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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