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Statistics in Business Introduction Statistics as an activity or discipline is concerned with the collection, organization, manipulation, interpretation and presentation of data (Anderson, Sweeney & Williams, 1994). A statistic on the others hand refers to a quantity that is derived from the analysis of a set of data. Alternatively defined, a statistic is a sample characteristic. Types and Levels of StatisticsThere are basically two types of statistics; inferential and descriptive (Anderson, Sweeney & Williams, 1994).
While inferential statistics involves the description of the population based on the results drawn from a sample, descriptive statistics involves the organization, description, and display of data such as in summary measures, graphs, and tables. When drawing inferences about a population, basically estimation and hypothesis testing is involved. Data may be quantitative or qualitative in nature. Qualitative data is data that is not numerical. Quantitative data on the other hand is numerical (involves numbers).
Data can be measured in four levels: nominal, ordinal, interval and ratio (Anderson, Sweeney & Williams, 1994). The lowest of the four levels of data measurement is nominal and deals with labels, categories or names. Data that falls under the nominal level is usually qualitative. At this level, the data cannot be ordered and statistics can not be reasonably drawn from it. The second level of data measurement is ordinal. At this level, the data can only be ordered and ranked with no room to make meaning of the differences between the data.
Data that can be ordered and in which sense can be made of their differences can be measured at the interval level. However, the data that falls in this category is known to have no starting point, examples being the Celsius and Fahrenheit scales used to measure temperature (Thompson, 2006). The highest level of data measurement is the ratio level. Data that falls in this category possesses all the characteristics of the interval level. In addition to these, the data has a zero value. Role of Statistics in Business Decision MakingStatistics plays an integral role in business decision making in the modern setup.
In order to make sound business decisions, for example, an entrepreneur should have a good idea about the demand for their products. Based on statistics, the quality of products produced by a business may be verified (Anderson, Sweeney & Williams, 1994). Furthermore, statistical data may be used by managers to establish or evaluate customer satisfaction, evaluate risks, calculate loss or profit, and calculate financial ratios among other applications, all of which may impact management decisions (Thompson, 2006).
Statistics Application ExamplesIn a soft drinks company, the company has to keep track of the quality of the soft drinks produced throughout the day. A sample of filled bottles is drawn at different times and their contents analyzed in a laboratory. In the event that it is discovered that a large number of the sample is of substandard quality, the management may decide to reject the entire batch assuming that it is mostly substandard. A marketing company may engage in market research to establish the extent to which potential customers like their products.
Based on the findings of the survey, the management may decide to make improvements on the product, maintain it as it is or altogether withdraw the product from the market. Managers of a business that produces standard size metal sheets in mass may need to order the resetting or maintenance machines if an analysis of the samples of finished products drawn from the production line reveals that many sheets are or different sizes or are larger/smaller than required. ReferencesAnderson, D., Sweeney, D.
& Williams, T. (1994). Introduction to Statistics: Concepts and Applications. New York. West Group.Thompson, B. (2006). Foundations of behavioral statistics. New York, NY: Guilford Press.
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