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Statistics and Decision-Making in Hrm

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Statistics and Decision-Making in Hrm
STATISTICS AND DECISION-MAKING IN HRM
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The word statistics has a Latin origin where the word status means state. Statistics is defined as the science that helps us understand how to collect, organize and interpret numbers or other information (data) about some topic (Bennett, et al., 2003). It is a discipline of data collection and summarizing to aid understanding and decision-making. It is also concerned with evaluation of the present status and predicting the future (Stockberger, 1996). Statistics studies the nature of a relationship between two or more variables of interest by using the numerical statistical data. Moreover only statistics makes it possible to analyze these relationships (Kachigan, 1986).

These features make statistics an essential component of every business system. Managers of modern world are more inclined to apply the standards of management based on concrete statistical data, widely applying statistics in support of the business policies and procedures. The collection and processing of data increases awareness of managers thereby improving business outcomes.

With further development during the twentieth century statistics became one of the fundamentals of management science. Management science is the discipline that employs scientific techniques of mathematical modelling and statistical analysis to help design systems and make better business management decisions that can enhance the business efficiency (Beer, 1967). Management science techniques presuppose making a research involving statistical data and analysis that enables a researcher to arrive at optimal solutions. These techniques are widely used in a modern business world for performance measuring and forecasting, quality control, operations planning and scheduling, as well as for the customer satisfaction management. Eventual technological advancement of information technology contributed to further integration of statistics into the management science to



References: Beer, A.S. (1967) Management Science: The Business Use of Operations Research. London: Aldus. Bennett, J.O., Briggs, W.L., Triola, M.F. (2008) Statistical Reasoning for Everyday Life 3rd ed. Boston, MA: Addison-Wesley. Dodge, Y. (2003) The Oxford Dictionary of Statistical Terms, Oxford: Oxford University Press. Heller, R. (2006) Management and Statistics: Never ignore the power of statistics in business management. Retrieved on 10 June 2011 from http://www.thinkingmanagers.com/management/management-statistics.php Hillier, F.S. & Lieberman, G.J. (2005) Introduction to Operations Research, 8th (international) edition, Boston, MA: McGraw-Hill. Kachigan, S.K. (1986) Statistical Analysis: An Interdisciplinary Introduction to Univariate and Multivariate Methods. New York, NY: Radius Press. Levin, R.I., Rubin, D.S. (1997) Statistics for Management, 7th ed. London: Prentice Hall. Mendenhall, W.(1975). Introduction to probability and statistics, 4th ed. North Scltuate, MA: Duxbury Press. NIsbett, R. E. (1993) Rules for Reasoning. Hillsdale, N.J.: L. Erlbaum Associates. Runyon, R.P., Haber, A. (1976). Fundamentals of behavioral statistics, 3rd ed. Reading, MA: Addison-Wesley Publishing Company. Stockberger, D. W. (1996). Introductory statistics: Concepts, models and applications. Retrieved on 24 June 2010 from: http://www.smsu.edu/  Taylor, S (2007) Business Statistics for Non Mathematicians

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