Management with Statistics in Life and Business
Statistical information is used in every area of life as we know it. Since life and business is all about management, we must be able to determine the value of our decisions. Statistics is used to measure the results of our decisions. Starting with one point in time and continually looking back to gauge our results, we are able to determine whether the path we are on is one of success or if we need to, possibly, change our approach. A review of where we have been is crucial since no one has the ability to forecast the future. We estimate our future outcome based on past performance.
Statistical information is used in every industry in every part of the world as well as a variety other disciplines. Here are a few that we will look at more closely later. Statistics are used by governments and all businesses including financial institutions. This list demonstrates the variety of disciplines that use statistics: economics, banking, accounting and auditing, natural and social sciences, and astronomy. Each of these areas needs to measure past performance so that future behaviors can be managed in order to give success a better probability of happening. An example from today’s news headlines is how statistical information is being gathered to use in order to correct negative behaviors created by bad regulatory governance and recession.
The international information provided to us in the data sets represents every major industry in our society to date. The top forty-eight economic countries based on Gross Domestic Product (GDP) includes every country that is a member of the Group of 20 (G20). The G20 is a group of twenty finance ministers and central bank governors from twenty major economies which contribute about 85% of the world’s economic growth based on GDP. What you see represented are categories such as petroleum producers, population measurements in 1000s, and percentage of population age 65 and over, average life expectancy, literacy rate, GDP per capita, labor force, unemployment rate, exports, imports, and cell phones. Analysis of the data in these categories helps measure economic feasibility as well as economic contribution by each country.
Real estate information provided here represents the average size and type of homes, including rooms and amenities, as well as how much the real estate was acquired for in price paid in thousands. The measurements here should be used against price. For example, in the first data set you see that this class represents a measure of how many bedrooms, square footage, pool or no pool, distance, township, garage, and number of bathrooms, against how much money you paid for that particular home. In this way you find the statistical average of what you should expect when purchasing a home in that particular area. An average is used since size in area is not easily comparable. If this tool was used as a measurement you would quickly determine if you were getting the deal of a lifetime or if you were being led to one of the worst financial decisions of your life.
Lastly we will look at the global financial data set provided. This information takes into account features about different companies, the economic sector and industry they occupy, their employees by the thousands, their sales in millions, cost of sales in millions, gross profit in millions, gross profit margin in percentage, total taxes in thousands, net income in thousands, return on assets in percentage, and return on investment in percentage. With this data set we are able to look at an array of variables to measure each company against either each other or against one of its competitors which lies within the same sector or industry, based on any one of the variables listed above. Then this could be used as a measurement for industry average or for the strength of a particular sector among a variety of industries.
Each of these data sets is vital to the measurement they represent. The measurement, usually displayed through visuals such as histograms, can portray the performance of variables against one common denominator. This common denominator is usually the point that one is trying to prove or push forward. For example, say you wanted to show the success rate based on production for each of the companies listed in the last data set versus the industry average. The industry average is the common denominator and the company’s performance is shown in relation to that common denominator.
Statistical information is a measurement from a starting point which passes through degrees of measurements moving forward; day, week, month, quarter, or even annual. These measurements are used daily in every part of our lives to evaluate the past and give the best prediction of what the future holds.
References
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G20 France 2011. New World of Ideas. www.g20.org n.d. Web. 28 Nov. 2011. http://www.g20.org/about_what_is_g20.aspx
"Importance of Statistics in Different Fields." EMathZone www.emathzone.com/
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Stiefel, L. 1990. Statistical Analysis for Public and Nonprofit Managers. NY: Praeger pg.169.
