1
Introduction
Chapter Outline
1.1 What Is the Value of Statistics?
Cigarette Smoking Causes CancerâTobacco Industry Denies Charges
North Carolina Congressional Districts GerrymanderedâAfrican Americans Slighted
Global WarmingâMyth According to the President
1.2 Brief Introduction to the History of Statistics
1.3 General Statistical Definitions
1.3.1 Statistical Notation
1.4 Types of Variables
1.5 Scales of Measurement
1.5.1 Nominal Measurement Scale
1.5.2 Ordinal Measurement Scale
1.5.3 Interval Measurement Scale
1.5.4 Ratio Measurement Scale
1.5.5 Summary of Terms
1.6 Additional Resources
Key Concepts
- General statistical concepts
Population
Parameter
Sample
Statistic
Descriptive statistics
Inferential statistics
- Variable-related concepts
Variable
Constant
Categorical variables
Dichotomous variables
Numerical variables
Discrete variables
Continuous variables
- Measurement scale concepts
Measurement
Nominal scale
Ordinal scale
Interval scale
Ratio scale
Welcome to the wonderful world of statistics! More than ever, statistics are everywhere. Listen to the weather report and you hear about the measurement of variables such as temperature, rainfall, barometric pressure, and humidity. Watch a sporting event and you hear about batting averages, percentage of free throws completed, and total rushing yard-age. Read the financial page and you can track the Dow Jones average, the gross national product (GNP), and bank interest rates. Turn to the entertainment section to see movie ratings, movie revenue, or the top 10 best-selling novels. These are just a few examples of statistics that surround you in every aspect of your life. This is not to mention the way statistics have, probably unnoticeably, influenced our everyday livesâjust consider the impact that statistics have had the next time you buckle your seatbelt or help a child into their booster seat.
Although you may be thinking that statistics is not the most enjoyable subject on the planet, by the end of this text you will (a) have a more positive attitude about statistics; (b) feel more comfortable using statistics, and thus be more likely to perform your own quantitative data analyses; and (c) certainly know much more about statistics than you do now. In other words, our goal is to equip you with the skills you need to be both a better consumer and producer of research. But be forewarned; the road to statistical independence is not easy. However, we will serve as your guides along the way. When the going gets tough, we will be there to provide you with advice and numerous examples and problems. Using the powers of logic, mathematical reasoning, and statistical concept knowledge, we will help you arrive at an appropriate solution to the statistical problem at hand.
Some students begin statistics courses with some anxiety, or even much anxiety. This could be the result of not having had a quantitative course for some time, apprehension built up by delaying taking statistics, a poor past instructor or course, or less than adequate past success, among other possible reasons. We hope this text will help alleviate any anxiety you may have. This is a good segue to discuss what this text is and what it is not. First, this is not a textbook on only one statistical procedure. This is a text on the application of many different types of statistics to a variety of disciplines. If you are looking for a text that goes very deep and into the weeds, so to speak, into just one area of statistics, then please review the Additional Resources sections at the conclusion of the respective chapters of interest. Although we feel we have provided a very comprehensive overview of and introduction into many types of statistics that are covered in the first few statistics courses, we do not pretend to suggest that everything you need to know about any one procedure will be covered in our book. Indeed, we do not know of any text that can make that claim! We do anticipate you will find the text is an excellent starting point, and should you desire to delve deeper, we have offered resources to assist in that endeavor.
Second, the philosophy of the text is on the understanding of concepts rather than on the derivation of statistical formulas. In other words, this is not a mathematical statistics textbook. We have written the book with the perspective that it is more important to understand concepts than to solve theorems and derive or memorize various and sundry formulas. If you understand the concepts, you can always look up the formulas if need be. If you do not understand the concepts, then knowing the formulas will only allow you to operate in a cookbook mode without really understanding what you are doing.
Third, the calculator and computer are your friends. These devices are tools that allow you to complete the necessary computations and obtain the results of interest. There is no need to compute equations by hand (another reason why we concentrate on the concepts rather than formulas). If you are performing computations by hand, find a calculator that you are comfortable with; it need not have 800 functions, as the four basic operations, sum, and square root functions are sufficient (one of our personal calculators is one of those little credit card calculators, although we often use the calculator on our computers). If you are using a statistical software program, find one that you are comfortable with (most instructors will have you use a program such as R, SPSS, or SAS). In this text, we do walk through basic formulas by hand so that you become acquainted with how the statistical program works and the numbers that are used in it. However, we donât anticipate (nor do we encourage) that you make a practice of working statistics by hand. Throughout the text, we use SPSS and R to illustrate statistical applications. Although this book is not a guide on all things SPSS and R, we do try to provide the tools you need to compute the various statistics. We hope that you will supplement what we provide with your own motivation to learn more about software that can assist you in computing statistics.
Finally, this text will take you from raw data to results using realistic examples. The examples may not always be from a discipline that is like the one you are in, but we hope that you are able to transfer or generalize the illustration to an area in which you more comfortable. These examples can then be followed up using the problems at the end of each chapter. Thus, you will not be on your own, but will have the text, a computer/calculator, as well as your course and instructor, to help guide you.
The intent and philosophy of this text is to be conceptual and intuitive in nature. We have written the text so that students who have completed basic mathematical requirements in high school can be comfortable reading the text. Thus, the text does not require a high level of mathematics, but rather emphasizes the important concepts in statistics. Most statistical concepts really are fairly easy to learn because (a) concepts can be simply stated, (b) concepts can be related to real-life examples, (c) many of the same concepts run through much of statistics, and therefore (d) many concepts can be related.
In this introductory chapter, we describe the most basic statistical concepts. We begin with the question, âWhat is the value of statistics?â We then look at a brief history of statistics by mentioning a few of the more important and interesting statisticians. Then we consider the concepts of population, parameter, sample, statistic, descriptive and inferential statistics, types of variables, and scales of measurement. Our objectives are that by the end of this chapter you will (a) have a better sense of why statistics are necessary, (b) see that statisticians are an interesting group of people, and (c) have an understanding of several basic statistical concepts.
1.1 What Is the Value of Statistics?
Let us start off with a reasonable rhetorical question: âWhy do we need statistics?â In other words, what is the value of statistics, either in your research or in your everyday life? As a way of thinking about these questions, consider the following headlines, which have probably appeared in your local newspaper.
Cigarette Smoking Causes CancerâTobacco Industry Denies Charges
A study conducted at Ivy-Covered University Medical School recently published in the New England Journal of Medicine has definitively shown that cigarette smoking causes cancer. In interviews with 100 randomly selected smokers and nonsmokers over 50 years of age, 30% of the smokers have developed some form of cancer, while only 10% of the nonsmokers have cancer. âThe higher percentage of smokers with cancer in our study clearly indicates that cigarettes cause cancer,â said Dr. Jason P. Smythe. On the contrary, âthis study doesnât even suggest that cigarettes cause cancer,â said tobacco lobbyist Cecil B. Hacker. âWho knows how these folks got cancer; maybe it is caused by the aging process or by the method in which individuals were selected for the interviews,â Mr. Hacker went on to say.
North Carolina Congressional Districts GerrymanderedâAfrican Americans Slighted
A study conducted at the National Center for Legal Research indicates that congressional districts in the state of North...