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Mathematical Concepts : Compression Analysis Of Heinz's Infant Sales Product

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Mathematical Concepts
To start, a marginal analysis* (MA) is beneficial. As noted, the PA facility operates at 40 percent of capacity. Assume that the all costs related to the 40 percent operations are estimated at $2 million per year, and during that time, the 14 SKUs are produced. If production costs were dou-bled, this would mean 28 SKUs at a cost of $4 million. Averaging the results from 2001-04 in Table 2, the middling infant sales total of Heinz’s products was $8.4 million (Heinz, 2014). For the MA, the estimated increase in costs is subtracted from the estimated increase in income, and since the increase in income outweighs the increase in cost, the expansion may be a wise invest-ment (Investopedia, n.d.). Another tool is a regression analysis* (RA). Before being able to test for a significance between price and volume of units, some data is required. Recall Table #1 illustrating the aver-age prices for a 16oz. unit of baby food from 2001-04; and Table #2 presenting Heinz’s infant sales during the same period. By assuming that all infant sales related to these jars, an estimation of the number of jars sold can be obtained by dividing the year’s infant sales by year’s average price. Table 3 presents these results. The estimated yearly percentage change in price may be ob-tained by averaging the differences from the previous years, and the same may be done for sales; see Table 4 for results. To test a significance between the two sets of variables, the RA is

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