ISOM 201 Excel assignment - Speech or Presentation Example

ISOM 201 Excel assignment SR1: Four local retailers (a) The following table shows excel output for values for mean, standard deviation, and confidence of variation, based on the AVERAGE AND STDEV functions, and direct division formula for confidence of variation.Table 1: Mean, standard deviation, and confidence of variationday 1ABCD15647271622138700340302812471502320525325646454027147283640882738456964452318102336612mean4039.24010standard deviation18.275676.42564317.262686.992059coefficient of variation 45.6891716.3919543.1566969.92059In comparing the four companies in terms of demand variability, I would use coefficient of variation instead of the standard deviation because of the former’s universality.

As Brase and Brase explain, standard deviation is only suitable for measuring deviations within a population. Samples from a single population are however, equivalent because sample mean is a good estimator of population mean. The means are however different among the retailers and means that the standard deviation is not a god measure for variability. The universal measure, coefficient of variation, which does not depend on units, is therefore suitable (109). Based on the coefficient of variation, the demand is more volatile for retailer D and least volatile for retailer B.

Retailer A experiences the second highest level of volatility and retailer C follows. (b)The following table shows the excel worksheet for the mean, standard deviation, and coefficient of variation for combinations of retailers with retailer D.Table 2: Combined retailers with retailer DADBDCD161616000121212202020444141414888666181818222564727213870403028715023253256454027283640273845644523233661mean2524.625SD19.9323915.9292219.52178coefficient of variability 79.7295464.7529278.08713From the results, and using either the standard deviation or coefficient of variation because of equivalent means, combining retailer B and retailer D, reduces the variability from 69.

9 percent to 64.75 percent. The other combinations increase variability of D. (c)The following excel output shows the correlation coefficients between the three combined retailers with retailer D.Table 3: Correlation coefficientAD1BD0.8916331CD0.3212410.6933221 B reduces variability the most because correlation coefficient.SR2: Three samplesFor the sample {1, 3, 5}Mean=(1+3+5)/3= 9/3= 3SD= {∑(x-µ)2/n-1}0.5xx-µ(x-µ)2(x-µ)2/n-11-24230005242{∑(x-µ)2/n-1=4And SD=40.5= 2Coefficient of variation= (2/3)*100= 67.

77 percent. Therefore,Mean=3, SD=2, CV=67.77For the sample, {3,3,3}Mean=(3+3+3)/3=9/3= 3For SD,xx-µ(x-µ)2(x-µ)2/n-1300030003000From the formula, therefore, SD=0 and CV=0. For the sample, {2,3,4}Mean=3, SD=1, CV= 33.33 percentThe following is the order of the samples with decreasing CV.(i), (iii), (ii)SR3: Aggregate forecastingSuppose demands for a local area are highly uncertain, it is more accurate to forecast corporate demands because this spreads the risk of error due to possible outliers from the volatile local area.

SR4: Mini case(a)Postponement tactic allows Benetton to meet uncertain demand of each color by reducing the level of uncertainty. By waiting until demand arises in a season, the company operates under certainty. Production is also done on demand and therefore to meet customers’ needs at a low inventory level.(b)With high level of uncertainty, the postponement strategy reduces volatility to establish accuracy in production volumes. This ensures reliable and valid data and the eliminated error, due to variation, in the production volumes, ensures accurate forecasts.

Works citedBrase, Charles, and Brase, Corrinne. Understanding statistics. Mason, OH: Cengage Learning, 2014. Print.