Sampling Process in Business: Components & Examples

Instructor: Scott Tuning

Scott has been a faculty member in higher education for over 10 years. He holds an MBA in Management, an MA in counseling, and an M.Div. in Academic Biblical Studies.

Statistics are an important tool used by business leaders to make solid, accurate business decisions. This lesson explores three important statistical concepts and explains their relevance in business decision-making activities.

True and Misleading Statistics

Have you ever watched the news or read an article that presents a statistic that seems so outlandish it couldn't possibly be true? For example, identify how the following statistics are both true and misleading at the same time. Finally, think about how an incorrect understanding of it might hurt a business.

Statement Qualifying Remarks
''More than 75% of people surveyed indicate that they support a tax increase to pay for public schools.'' The study was conducted by the teacher's union and surveyed only teachers.
''A recent study indicate that nearly 90% of Americans identify themselves as either somewhat or very religious.'' The survey included only three questions, and the only alternative to ''somewhat'' or ''very'' was ''not religious at all.''
''Only a paltry 16% of city residents support a permit for a big box retailer to build in town.'' The village is a small resort community in the pristine mountains with a permanent population of only 800 persons.

In some form, these statements are both true and false at the same time. Let's look at some statistical values that can help business leaders become better consumers of market research data.

Determining if Results are Actionable

As you thought about the statements above, what consequences of poor interpretation came to mind? In the fist case, it might lead to politicians supporting or opposing something their constituents do not.

The second might lead a religious bookseller opening a store in a location that does not have a sufficient customer base.

The third could lead a retailer to withdraw from a deal, when in reality, tourism and seasonal residents would more than support it. With that in mind, let's look at how confidence intervals, point estimates, and degrees of freedom can help reduce the likelihood of inaccurate interpretations of data.

Confidence Intervals

Have you ever heard someone use the expression, ''Even a broken clock is right twice a day.''?

In a sense, this statement captures the importance of the confidence interval, a value that quantifies the risk of a random false positive. In technical terms, it describes the chances that one would adopt or reject a hypothesis (statistical question) incorrectly.

If we look again at the clock, the confidence interval could be illustrated like this:

As a call center supervisor, an employee points out that a break room clock is not working. However, when you walk in to look, the clock displays the exact time that is shown on your own watch. Your likely response is to let the employee know that the clock is in working order.

But how 'confident' are you that your analysis that the clock is not, in fact, broken? Are there any conditions under which your check of the clock would not have given you an accurate representation?

Example Table for Confidence Interval

The answer, of course, is yes. In fact, there are two ways the clock could appear to be working when it is, in fact, broken. One is that your watch and the break room clock just happened to stop at the exact same time. The second is that you happened to walk into the room and check your watch some multiple of 12 hours after it stopped.

Because an occurrence like this is exceedingly rare, you have a high confidence that your hypothesis is accurate. Your hypothesis is essentially: if my watch agrees with the clock, then the clock cannot be broken. In statistics, a confidence interval quantifies just how sure the researcher is that he or she is not going to inappropriately accept or reject a hypothesis.

Degrees of Freedom

If you were a business owner, would a 29% rise in wages and salaries expense concern you? It most definitely should - unless you own a ski resort.

Imagine being an HR professional in an organization like a ski resort. Your workforce consists of mostly full-time temporary seasonal workers, and the number of days you employ these individuals varies based on how many days the resort is in operation during a winter season. Some years, the resort enjoys upwards of 118 operating days. In other years, it may operate only 88 days.

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