Learning statistics like learning a language, May 26, 2006, 2D.

When many people think about statistics, they often cringe.  Reasons for this are probably widely varied.  Some people may have phobias that have followed them into their adult lives from their mathematics and quantitative courses in high school or college.  Some may be intimidated by the complex sounding lingo of the field.  Others may avoid ever approaching the topic due to beliefs that the concepts are too difficult to learn, that conclusions can be manipulated to meet the will of the investigator, or that the techniques are not really useful.  In the view of many, “statistic” and “sadistic” are two words that can be used interchangeably. 

In reality, none of those are valid reasons to avoid or shun statistics.  While statistics involves the use and manipulation of numbers, the emphasis for practitioners is not on mathematics, but on interpretation and analysis of validity.  Computers can now perform complex mathematical computations quickly and accurately.  It is now most important for users of statistics to understand how to apply statistical tools and techniques and to interpret results.  Mastering these concepts can help managers in their jobs. 

Managers are problem solvers.  When confronted with exceptions to established work processes, managers step in to resolve the exceptions with their organization’s best interests in mind.  If there were no organizational problems, the manager’s job would be that of an engineer.  The manager would simply designate a level of performance, adjust the appropriate controls on the “machine,” turn on the machine for a determined time, and then turn off the machine at the end of the day.  Periodically, the manager would have to perform maintenance or repair and occasionally upgrade the equipment with a better model.  There are very few organizations that operate like machines.  Most managers deal with work process problems, individual problems, group problems, organizational problems, and problems that arise from sources outside the organization.   A manager’s job is very complex—a variety of skills, competencies, and problem solving tools are needed to be successful.

Statistics is a decision-making tool.  It is a way to draw information from data—which is then used by managers and decision-makers to solve organizational problems.  There are two basic types of statistics, descriptive and inferential.  Descriptive statistics “describe” the data (the number of data points, the middle of the data range, the dispersion of numbers, etc.).  Inferential statistics is more complex than descriptive statistics because it involves “inferring” measures drawn from a sample to a population.  A host of errors and threats to validity can creep into inferential statistics.  Conclusions are drawn using the notions of sampling theory and probability.

With a little time and effort, almost anyone can learn the fundamental tools and techniques of statistics.  In many ways, learning statistics is like learning a language—a language that uses numbers, logic, and scientific analysis.  The conclusions drawn from properly conducted statistical analyses provide sources of information for managers that cannot be gained solely from experience, intuition, or professional judgment.  

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