How To Measure The Forecast Results Essay Assignment Paper

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**1) Product structure tree**Product structure tree is a various leveled decomposition of an item, commonly known as a bill of materials. With the help of product structure, comprehension of the parts which create a product and their properties can be described. It incorporates raw materials, assemblies, equipment, components and different items in a progressive structure that shows a grouping of things that meet up at a phase in the assembling procedure. In the initial phase of the design of the product, engineers start the design by drawing out a structure for the item which distinguishes the major items and frameworks that will combine to make the intended product. For every segment, existing and already composed parts must be assessed for their capacity to give the vital function. Advantages of product structure are provided below: 1. It helps to focus on particular market portions. 2. Address the issue of clients efficiently and effectively. 3. Broaden learning and expertise inside particular divisions. 4. React to change of market more rapidly and adaptable. 5. Energize positive competition between different departments. 6. Facilitate and measure the performance of every division specifically. There are certain disadvantages of product structure also which are provided below: 1. It involves duplication of functions and assets. 2. Scatters technical expertise over littler units. 3. Supports negative contentions among divisions. 4. It overemphasizes divisional goals. 5. Loses focal control over each different division. Product structure is appropriate especially for big companies with at least two product lines, key clients or markets How To Measure The Forecast Results Essay Assignment Paper

It can better be understood by an example. Suppose that the final product A is a result of assembly of one item B, two items C and four items D. Also B is composed by assembling two components E and F. than product structure tree for assembly of A will be as follows:

As the list of parts and components of bill of materials is displayed in clear and hierarchal manner into making the product, in order to compute what parts are needed from the given existing inventory,

**by working backwards**, parts, materials and components are determined so that they can be ordered or produced on time, without hindering the Master Production Schedule.Usually computer programs are used in order to reduce errors and perform calculations more accurately and speedy. Integral part of ERP systems, WinQSB modules are also used for solving MRP problems.

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**The weighted moving average (WMA) is a technical indicator that assigns a greater weighting to the most recent data points, and less weighting to data points in the distant past. The WMA is obtained by multiplying each number in the data set by a predetermined weight and summing up the resulting values. Traders use weighting moving average to generate trade signals, to indicate when to buy or sell stocks.**## ORDER NOW

The weighted moving average (WMA) is a technical indicator that traders use to generate trade direction and make a buy or sell decision. It assigns greater weighting to recent data points and less weighting on past data points. The weighted moving average is calculated by multiplying each observation in the data set by a predetermined weighting factor.

Traders use the weighted average tool to generate trade signals. For example, when the price action moves towards or above the weighted moving average, the signal can be an indication to exit a trade. However, if the price action dips near or just below the weighted moving average, it can be an indication of a favorable time to enter a trade

Simple is you add up all the values, then divide by the total number of values.

Weighted is when values take different importance, so you multiply by their weight (importance) then sum it all up, then divide by the total weight. How To Measure The Forecast Results Essay Assignment Paper

Example:

7 with weight 3

8 with weight 2

10 with weight 4

The sum of the weights is 3+2+4= 9. The sum of the weighted values = 7 x 3 +8×2+10 x 4 = 21+ 16+40= 77. The weighted average is 77/9 = 8.55

“To find your weighted average, simply multiply each number by its weight factor and then sum the resulting numbers up. For example: The weighted average for your quiz grades and term paper would be as follows: 82(0.2) +90(0.35) + 76(0.45)= 16.4 +31.5+ 34.2 82.1.”

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**Final answer**

3)

The absolute and mean absolute deviation show the amount of deviation (variation) that occurs around the mean score. To find the total variability in our group of data, we simply add up the deviation of each score from the mean. The average deviation of a score can then be calculated by dividing this total by the number of scores. How we calculate the deviation of a score from the mean depends on our choice of statistic, whether we use absolute deviation, variance To find out the total variability in our data set, we would perform this calculation for all of the 100 students’ scores. However, the problem is that because we have both positive and minus signs, when we add up all of these deviations, they cancel each other out, giving us a total deviation of zero. Since we are only interested in the deviations of the scores and not whether they are above or below the mean score, we can ignore the minus sign and take only the absolute value, giving us the absolute deviation. Adding up all of these absolute deviations and dividing them by the total number of scores then gives us the mean absolute deviation (see below). Therefore, for our 100 students the mean absolute deviation is 12.81, as shown below:

mean absolute deviation= ΣΙΧ – μ| /N

= 1281 / 100

= 12.81

Where µ = mean, X= score. = the sum of, N = number of scores. [X=”add up all the scores. 11 take the absolute value (ie. ignore the minus sign).

The Mean Squared Error

**measures how close a regression line is to a set of data points**. It is a risk function corresponding to the expected value of the squared error loss. Mean square error is calculated by taking the average, specifically the mean, of errors squared from data as it relates to a function.It is a term in regression that indicates the mean of the squared deviations of the value predicted by the regression equation from the actual value: How To Measure The Forecast Results Essay Assignment Paper

Σ (yi-yi^)

^{2}/n,where

yi is the actual value of y for case i

yi is the value of y for case i predicted by the model

n is the number of points.

Mean error is the average of all errors in a set. An “error” is a difference in measurements between an observation and a true value

**The mean error usually results in a number that isn’t**

**helpful**because positives and negatives cancel each other out.

For Example, two errors of +100 and -100 would give a mean error of zero:

**mean = sum of all values/number in the set**

**= (+100 + -100) / 2**

**= 0 / 2**

**= 0.**

Zero implies that there is no error, when that’s clearly not the case for this example.

How To Measure The Forecast Results Essay Assignment Paper