By Whitney Robare, Guest Contributor
What emotions come to mind when you think of statistics. You may be surprised to know many people have a healthy fear of the topic. Think about the number of people who are stressed about the idea of rendering any type of calculation.
So many math fearful students go their entire academic career trying to dodge higher level math by choosing to study various sciences they believe to be devoid of calculations. I know this fact to be true. I was one of those people! As I made my journey through an undergraduate degree and then graduate school, I found a growing reliance on statistics and statistical principles. They are a necessary evil.
Statistics is the grammar of science.
– Karl Pearson
Statistics, by definition, are numbers used to describe data or relationships. Relationships are prevalent in all industries. Many professionals rely directly on statistical relationships. We use statistics to make decisions, to answer questions, and to forecast. Statistical data keeps us informed and are key factors to everyday life.
We live in a world full of information which needs to be properly processed and analyzed. Statistics can guide how we collect data, analyze data, and how results are presented. Having a basic understanding of the underlying statistical analysis which drives our professions can make a world of difference in the workplace.
This discussion will show you how statistical anxiety, or statics phobia, is real. Statistics are not simply a useless topic, but a subject which should be embraced by all.
So, how do statistics play a role in our everyday life? We use statistics to make predictions about future events. We use statistical data in quality testing. Ever watched a weather forecast on TV? Yet another way statistical data creeps into our daily lives. Preparedness for communicable disease situations is a great example of how statistics is used in the medical field. In the political arena, statistics help campaign teams know the probability of their chances of success in a specific area. Statistics are used in figuring out insurance premiums and the fitness of candidate for coverage. Statistics are used to help stock consumer goods at your local retailer or grocer. Decisions made in the financial markets are often based on underlying statistical principles. Sports is another area that famously relies on statistics to choose favorites and calculate averages.
“Most people use statistics like a drunk man uses a lamppost; more for support than illumination.”
– Andrew Lang
In olden days, it is understandable why statistics gave students and professionals dread. Having to memorize formulas and work through tedious calculations. Sitting through theoretical examples that lacked practical relevance. But with the introduction of statistical software like MiniTab, students and practitioners alike can now understand important concepts without losing themselves in massive details.
No longer are students burdened with computational gymnastics and formulas. Real data sets can be studied which allow for identifying practical situations to use statistics. Mini tab allows data to be plotted in a various ways and simulations can be run and used as learning tools.
Let’s stop thinking of statistics as a useless topic and embrace them. Although the language of statisticians seems somewhat different and strange, it doesn’t mean that everything they share is incomprehensible. Rest assured that statistical communication is a challenge for both sides due to the terms involved. Understand that many of the terms used in statistics mean something else in plain English. The misunderstandings that occur are easily combated by garnering an understanding of basic statistical terms. So, let’s stop thinking of statistics as other worldly and realize the everyday relevance and practicality. The following are just a few of basic statistical terms and their meanings.
“Statistical thinking will one day be as necessary a qualification for efficient citizenship as the ability to read and write.”
– H.G. Wells
- Mean is the sum of all the values in your data set divided by the number of values. If you role the dice 7 times and get 10, 2, 8, 10, 4, 6, and 9 – the total is 49 and the mean is 7. For those living normal lives, outside the world of statistics, the mean is referred to as the average. Be warned, no self-respecting statistician would ever use the word average.
- Mode is the most frequent value in a data set. For our 7 roles of the dice, we got 10 twice and all the other values just once. Our mode is 10.
- Median a data set’s middle value, found after you sort the values from low to high. Our roles of the dice gave us 2, 4, 6, 8, 9, 10, and 10. The middle value, or median, is 8.
- NORMAL is data that follows a bell-shaped curve. Within normal limits means that the results are within the range of what is considered normal.
- POWER is the capability to detect a significant effect. Power is the probability that a statistical test will detect differences when they truly exist. Think of Statistical Power as having the statistical “muscle” to be able to find differences between the data sets you are studying, or making sure you do not “miss” finding differences.
- RANDOM is a sample captured such that all individuals in a population have equal odds of selection. In statistics, a random variable is an assignment of a numerical value to each possible outcome of an event space. This association simplifies the identification and the calculation of probabilities of the events.
- RANGE is the difference between the lowest and highest values in a data set. The range of a set of data is the difference between the largest and smallest values. Differences are exact, the range of a set of data is the result of subtracting the smallest value from largest value.
- REGRESSION is predicting one variable based on the values of other variables. Simple regression is used to examine the relationship between one dependent and one independent variable. After performing an analysis, regression statistics can be used to predict the dependent variable when the independent variable is known.
- RESIDUALS is the difference between observed and fitted values. A residual value is a measure of how much a regression line vertically misses a data point. You can think of the lines as averages; a few data points will fit the line and others will miss. A residual plot has the Residual Values on the vertical axis; the horizontal axis displays the independent variable.
- SIGNIFICANCE is the odds that the results observed and fitted values. Statistical significance is the likelihood that a relationship between two or more variables is caused by something other than chance.
– Peter Drucker
Having a solid foundation in basic statistics will go a long way in using advanced statistical software like mini tab. Don’t simply rely on knowing how to use the software and being vaguely familiar with terms, rather, strive to understand what the software is really doing for you. Often time statisticians share their findings with those that are not well versed in the art of statistics. There is a need to instill greater statistical understanding amongst the general population.
So how do we best use statistics to our advantage? The use of statistics in business enables managers to handle their role better by making evaluation of performance and performance management easier. This is done through managers gathering data about a worker’s performance or a products performance. This can be based on the number of responsibilities accomplished or, the number of units sold, or feedback received from testing. There are various forms of output that can be used. Managers need only find and analyze the data and apply specific statistical principles.
– John Ruskin
About Whitney Robare
Whitney is a military wife, mother of two, and an MBA student at Louisiana State University Shreveport. She is a travel lover, a planner of all things, and a fitness enthusiast. Her days are controlled chaos which involve coordinating her family’s busy schedules, trotting the globe on grand adventures, and studying for exams.
Whitney also works in Airport Operations Management and has done so, off and on, for the past 10 years. She earned her Bachelors Degree in Aviation Management from Hampton University and has served on their Aviation Advisory Board.
“Quality means doing it right, when no one is looking.”
– Henry Ford
What is Quality Function Deployment? from the American Society for Quality (ASQ)
Quality Function Deployment from ScienceDirect