Complete business statistics by Amir Aczel, Jayavel Sounderpandian PDF

By Amir Aczel, Jayavel Sounderpandian

ISBN-10: 0077239695

ISBN-13: 9780077239695

Statistical integrity with an entire Excel resolution. The 7th variation keeps its worldwide emphasis, keeping its place of being on the leading edge of foreign matters in enterprise.

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The following spreadsheet is set up to calculate the deviations from the target, SSD(Target), and the Average SSD(Target). Column B contains the data, showing a process mean of 2,004. (Strictly speaking, this would be sample data. 5. In the range G5:H13, a table has been created to see the effect of changing the target on Average SSD(Target). The offset refers to the difference between the target and the process mean. 1. Study the table and find an equation that relates the Average SSD to VARP and the Offset.

Set Mult ϭ 1 and Add ϭ 5, which corresponds to adding 5 to all data points. Observe how the statistics have changed in the modified statistics column. Keeping Mult ϭ 1 and changing Add to different values, observe how the statistics change. Then make a formal statement such as “If we add x to all the data points, then the average would increase by x,” for each of the statistics, starting with average. 2. Add an explanation for each statement made in part 1 above. For the average, this will be “If we add x to all the data points, then the sum of all the numbers will increase by x *n where n is the number of data points.

Call this 2,004 cm3 the process mean. The damage from process errors is determined by the deviations from the target rather than from the process mean. The variance, though, is calculated with deviations from the process mean, and therefore is not a measure of the damage. Suppose we want to calculate a new variance using deviations from the target value. Let “SSD(Target)” denote the sum of the squared deviations from the target. ] Dividing the SSD by the number of data points gives the Average SSD(Target).

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Complete business statistics by Amir Aczel, Jayavel Sounderpandian

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