When you were in school, you probably asked the question, why do I have to take statistics?” Your adviser told you: “because it’s required for the degree.” “But why,” you said “why would I ever need to use statistics?”

Everybody who has completed high school has learned some statistics. There are good reasons for that. Your class grades were averages of scores you received for tests and other efforts. Most of your classes were graded on a curve, requiring the concepts of the Normal distribution, standard deviations, and confidence limits. Your scores on standardized tests, like the SAT, were presented in percentiles. You learned about pie and bar charts, scatter plots, and maybe other ways to display data. You might even have learned about equations for lines and some elementary curves. So by the time you got to the prom, you were exposed to at least enough statistics to read USA Today. In college, you’ll find that most majors require some statistics. Why? Consider the following.

Statistics is an integral part of everyday life in America. Without statistics, there would be no U.S. Census, IRS audits, Nielsen ratings of TV shows, political polls, and consumer preference surveys. Our society couldn’t function without being able to figure out tax brackets, insurance rates, stock prices, and online matchmaking. We couldn’t predict the outcome of elections before the polls close. There would be no standardized tests, no ACT, GRE, TOEFL, MBTI, or CATs (MCAT, LCAT, PCAT, and VCAT). Amazon.com couldn’t tell us what we want to buy. Baseball announcers would have nothing to talk about between pitches. It would be anarchy.

If you’re still not convinced that you need to learn statistics, keep reading.

The use of statistics is common to almost all fields of inquiry—social and natural sciences, sports, business, education, library and information science, and even music and art. Its popularity is attributable at least in part to its applicability to any type of data. Statistical methods can be used for analyzing data based on natural laws, theories, or nothing in particular. If you can measure it, you can analyze it with statistics. If you’re creative enough, you can even analyze things you can’t measure very well.

So why do your advisors want you to take statistics? Here are a few of the reasons.

Statistics provide a starting point and a course of action —If you’re in the natural sciences, you’ll probably have some basic principles, laws, or at least theories to start with in analyzing data. Even some of those were discovered or verified by statistical observation. If you’re in the social sciences, business, economics, or most other fields, though, you’re got little to go on besides statistics. Anecdotes aren’t worth much. Statistics gives you a place to start by having you focus on the population, so you know what to sample, and the phenomenon, so you know what to measure and how to measure it. Once you have laid this groundwork, statistics has you define alternative hypotheses to weigh and provide a variety of methods to analyze the data.

—If you’re in the natural sciences, you’ll probably have some basic principles, laws, or at least theories to start with in analyzing data. Even some of those were discovered or verified by statistical observation. If you’re in the social sciences, business, economics, or most other fields, though, you’re got little to go on besides statistics. Anecdotes aren’t worth much. Statistics gives you a place to start by having you focus on the population, so you know what to sample, and the phenomenon, so you know what to measure and how to measure it. Once you have laid this groundwork, statistics has you define alternative hypotheses to weigh and provide a variety of methods to analyze the data. Statistics give you more ways to analyze data — Statistics is a colossal workshop with more tools than you could ever use in a career. Statistics allows you to describe, correlate, detect differences, group, separate, reorganize, identify, predict, smooth, and model. And it’s not just the variety of tools for doing different things, there are also many tools for doing the same thing in different ways. Want to find the center of a data distribution? You can use the arithmetic mean, the geometric mean, the harmonic mean, trimmed and winsorized means, weighted means, the median, the trimean, or the mode. Each has its own special use, like the variety of types of screwdrivers used by a mechanic. With a statistician’s toolbox, you can gain far more insight from your data than you might from any other type of analysis.

— Statistics is a colossal workshop with more tools than you could ever use in a career. Statistics allows you to describe, correlate, detect differences, group, separate, reorganize, identify, predict, smooth, and model. And it’s not just the variety of tools for doing different things, there are also many tools for doing the same thing in different ways. Want to find the center of a data distribution? You can use the arithmetic mean, the geometric mean, the harmonic mean, trimmed and winsorized means, weighted means, the median, the trimean, or the mode. Each has its own special use, like the variety of types of screwdrivers used by a mechanic. With a statistician’s toolbox, you can gain far more insight from your data than you might from any other type of analysis. Statistics examine both accuracy and precision —Any marksman will tell you that it’s not enough to be able to hit a target. You have to be able to hit it where you aim and do it consistency. That’s accuracy and precision. Many analytical techniques focus on accuracy and forget all about precision. But variability, uncertainty, and risk don’t go away by just ignoring them. Statistics is all about understanding variability.

—Any marksman will tell you that it’s not enough to be able to hit a target. You have to be able to hit it where you aim and do it consistency. That’s accuracy and precision. Many analytical techniques focus on accuracy and forget all about precision. But variability, uncertainty, and risk don’t go away by just ignoring them. Statistics is all about understanding variability. Statistics examine both trends and anomalies —Most forms of analysis focus on finding similarities and patterns in data. Statistics, in particular, can be used to find linear and nonlinear trends, cycles, steps, shocks, clusters, and many other types of groupings. What’s more, statistics can be used to identify and explore divergent or anomalous cases, which don’t fit general patterns. Sometimes it is these outliers rather than the trends that reveal the information most crucial in an analysis.

—Most forms of analysis focus on finding similarities and patterns in data. Statistics, in particular, can be used to find linear and nonlinear trends, cycles, steps, shocks, clusters, and many other types of groupings. What’s more, statistics can be used to identify and explore divergent or anomalous cases, which don’t fit general patterns. Sometimes it is these outliers rather than the trends that reveal the information most crucial in an analysis. Statistics tells you how much information you need —In data analysis, more is not always better. It’s not unusual to have too much data to make sense of using only graphs and tables. Statistics provides a variety of ways to help you decide about how many samples you need to achieve a certain objective. Statistics provides ways to judge the quality of the data and compensate for misleading variability. Statistics can also tell you if your data are redundant, and if so, provide ways to reassemble the data more efficiently.

—In data analysis, more is not always better. It’s not unusual to have too much data to make sense of using only graphs and tables. Statistics provides a variety of ways to help you decide about how many samples you need to achieve a certain objective. Statistics provides ways to judge the quality of the data and compensate for misleading variability. Statistics can also tell you if your data are redundant, and if so, provide ways to reassemble the data more efficiently. Statistics provide standardization— You can usually convince people who are reviewing your work that your data analysis is legitimate because it uses well-known, professionally accepted, statistical procedures. Likewise, it’s easier to use statistics as the basis for any standardized procedures you specify that others use because most people know some statistics. For example, Government regulations frequently require the use of statistics to report and analyze data sets, such as crime rates, pharmaceutical effectiveness, environmental impact, occupational safety, public health, and educational testing.

So you see, statistics has a lot to offer you, whether there is a strong theoretical basis to your field of practice or not. That’s why your advisers want you to learn about it.

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