Application of descriptive statistics

Application of descriptive statistics Descriptive statistics is one of the statistical approaches to data analysis for informed ‘ decision-making’. This application is particularly important to business organization for ‘ evidence-based’ judgments. The statistics also facilitates evaluation of an organization’s performance based on analysis of achieved results. This paper seeks to discuss application of descriptive statistics in a business set up. Using the business environment at Daimler, the paper explores application of descriptive statistics in ‘ decision-making’.
Descriptive statistics offers a summary of distribution of data. One of the applications of descriptive statistics is in grouping of large sets of data for easy understanding of trend. The case of Diamler that includes transactions in large numbers of vehicles for instance requires summaries that group sets of data for clarity. Frequency distribution tables and histograms groups data and illustrate frequencies of each group of data. Yearly demand for a particular brand of vehicle that can be grouped by seasons or months allows the company to determine the trends in seasonality of demands for its products. As a producer, frequency distribution tables, graphs and histograms helps the company to predict trend and hence determine its production capacity. This facilitates on time demand production and help to save costs of storing stock. Similarly, frequency distribution by geographical markets helps the company to understand the market capacity. This is useful in making decisions over distribution of the company’s products in its markets. These analyses help the company to make informed decision of its trend in supply (Ross, p. 10-17; Daimler, p. 1).
Measures of central tendencies are other descriptive statistics that facilitates business ‘ decision-making’ processes. The mean, for example, illustrates the average values recorded over a subject in a given period. Its application in Daimler is realized through average demand for different vehicle brands across seasons. Among other factors, understanding mean distribution facilitates decisions on production capacity in order to meet the market’s demand without underproduction or underproduction. The mode, another descriptive statistics, defines the highest frequency in grouped data. The company uses it to identify peak seasons and locations for demand of each of its vehicle brands. This helps the company to maximize on its market by availing sufficient stock in its markets (Mimmack and Meyer, p. 10- 19).
Standard deviation is another important descriptive statistics that is used by Daimler Company. The standard deviation is a measure of dispersal that identifies the average deviation of values from the mean value. It shows how a variable is expected to deviate from its expected value. An example of application of standard deviation by the company involves setting intervals for predictions and forecasts. With the help of analysis of other descriptive statistics, the company predicts its expected sales for a product in a period. Standard deviation is then used to provide for a range within which the company can expect to meet demand for each of its products (Mimmack and Meyer, p. 23).
Descriptive statistics offers features of data for clarity that aids ‘ decision-making’. Examples include frequency distributions tables, histograms, mean, mode, and standard deviation. Daimler applies these statistics to make decision on its productivity level in order to maximize on its demand with minimum storage wastes.
Works cited
Daimler. Company. Daimler. 2012. Web. 10 April 2012. Mimmack, Gillian, and Meyer, Denny. Introductory Statistics for Business. Cape Town, South Africa: Pearson South Africa, 2001. Print
Ross, Sheldon. Introduction to Probability and Statistics for Engineers and Scientists. California, CA: Academic Press, 2009