# Otto's Consulting Report

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Otto’s Auto Parts Statistical ReportHansen Consulting proudly presents the following statistical information for Otto’s Auto parts. Statistics is a branch of mathematics that makes it possible for you to gain an edge over your competitors by providing a method for collection of data, and a way to summarize and quantify it to represent real world observations from which predictions can be made. Statistics also includes stochastic modeling, which is a powerful tool that incorporates random variables to predict future outcomes. For decades insurance companies have successfully profited from using stochastic modeling for making predictions of unknown entities. Stochastic models can be run hundreds or even thousands of times to show the

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Descriptive statistics only provides information about the group the data was taken from. Whereas, statistical estimation is used to extend the results from the sample to a larger group in order to make estimates about the population from which the samples were taken. One useful way of summarizing data is through the use of graphs and charts. We created a pie chart (located on the next page) to illustrate an estimated percentage of the workforce that are male and the percentage that are female from a random sampling of 36 factory employees selected by your personnel department for our statistical study.

From the given set of sample data, we calculated that there is a 95% probability that the estimated proportion of the males from the population of 800 factory workers, is between 45% and 77%. This calculation was derived from statistical estimation, and in this case it simply gives you an estimated range of values that is likely to include an unknown population segment (percentage of males). To put it another way, if we conducted 100 different random samplings of 36 workers, 95 of those sampling’s would produce a percentage of the male workers that would fall between 45% and 77%, while the other 5 samplings would be either higher or lower than our calculated values.

Employee profile – age

Descriptive statistics was used to summarize the data collected pertaining to age among the 36 employees that were sampled. The average

From the given set of sample data, we calculated that there is a 95% probability that the estimated proportion of the males from the population of 800 factory workers, is between 45% and 77%. This calculation was derived from statistical estimation, and in this case it simply gives you an estimated range of values that is likely to include an unknown population segment (percentage of males). To put it another way, if we conducted 100 different random samplings of 36 workers, 95 of those sampling’s would produce a percentage of the male workers that would fall between 45% and 77%, while the other 5 samplings would be either higher or lower than our calculated values.

Employee profile – age

Descriptive statistics was used to summarize the data collected pertaining to age among the 36 employees that were sampled. The average