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The purpose of this essay is to examine the purpose of statistics in business. Our text, Lind (2011) defines statistics as “The science of collecting, organizing, presenting, analyzing, and interpreting data to assist in making more effective decisions” (p.5). Types and levels of statistics

There are two major types of statistics, descriptive and inferential. Descriptive statistics is defined by Lind (2011) as “methods of organizing, summarizing, and presenting data in an informative way” (p.6). An example of descriptive statistics would be a high school report showing that it had 300 graduates in 1990 and 450 graduates on 1991. The information that they provided described the amount of graduates that they had for each year. Inferential statistics is defined by Lind (2011) as “the methods used to estimate a property of a population on the basis of a sample” (p.7). If the same high school sent out a report showing the graduate numbers for 1999- the present to estimate the number of graduates that they would have for this school year, those statistics would be inferential because they are used to estimate future outcomes.

There are four levels of statistical data: nominal, ordinal, interval and ratio. The nominal level deals with qualitative variables such as colors and blood types that can only be counted and classified. Ordinal data measurement is a variable rating system that ranks data according to predetermined categories that have only relative values such as poor, average, and good. Data can be ranked and ordered using this method. Interval data measurement adds to the ordered level by adding the characteristic of a consistently measured differential.

A thermometer is an interval measurement tool. Differences in degrees of temperature are consistent between the level intervals. The last level of statistics is ratio-level data; this is used for quantitative data recording. It builds upon the interval measurement by adding that “point 0 is meaningful and the ratio between two numbers is meaningful” (p.13). An example of ratio level data would be weight. A scale is calibrated at “0” and is measured in increments of one pound or kilogram to determine a person’s weigh or the difference of weigh between two individuals or products.

The role of statistics in business

Statistics are the lifeline of a business. A business relies on good statistical data to determine its financial standing, projecting future sales and projects, and to provide the management team with information to make sound business decisions. When we look at statistics in the business world we are primarily concerned with their bearing on profits, investments, hours worked, and wages. The decision making process is made easier by analyzing data to determine the best course of action instead of taking uneducated risks.

An example of the importance of statistics in business would be forecasting. We recently hired additional personnel based on historical data on first quarter sales and average call handle time of our phone staff. We took the archived data that showed how many calls were taken in our call center, the number of personnel on the phones, and the average time of each call. We used this historical information from the last three years to determine how many people we will need on the phones at any given time during first quarter. This data allowed us to be proactive in staffing and fund allocation to meet the needs of our customers and phone staff.

Conclusion

Statistics play a vital role in the business world. We are a smarter and more intuitive society of decision makers because of statistics. A business is more stable when the guess work is taken out of the equation and replaced with data analysis that produces sound business decisions and planning.

References

Lind, D., Marchal, W., & Wathen, S. (2011). Basic statistics for business and economics (7th ed.). New York, NY: McGraw-Hill/Irwin.

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