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In the numbers explosion all around us in our modern-day dealings, the buzzword is data, as in, “Do you have any data to support your claim?” “The data supported the original hypothesis that . . .” and “The data bear this out. . . .” But the field of statistics is not just about data. Statistics is the entire process involved in gathering evidence to answer questions about the world, in cases where that evidence happens to be numerical data.
Statistics For Dummies is for everyone who wants to sort through and evaluate the incredible amount of statistical information that comes to them on a daily basis. (You know the stuff: charts, graphs, tables, as well as headlines that talk about the results of the latest poll, survey, experiment, or other scientific study.) This book arms you with the ability to decipher and make important decisions about statistical results, being ever aware of the ways in which people can mislead you with statistics. Get the inside scoop on number-crunching nuances, plus insight into how you can
This down-to-earth reference is chock-full of real examples from real sources that are relevant to your everyday life: from the latest medical breakthroughs, crime studies, and population trends to surveys on Internet dating, cell phone use, and the worst cars of the millennium. Statistics For Dummies departs from traditional statistics texts, references, supplement books, andstudy guides in the following ways:
Chances are, Statistics For Dummies will be your No. 1 resource for discovering how numerical data figures into your corner of the universe.
More Reviews and RecommendationsDeborah Rumsey earned her Ph.D. in statistics from Ohio State University (OSU) in 1993. Upon graduating, she joined the faculty in the Department of Statistics at Kansas State University, winning the distinguished Presidential Teaching Award and earning tenure and promotion in 1998. In 2000, she returned to OSU as the Director of the Mathematics and Statistics Learning Center, where she is today. Deb is the Editor of the “Teaching Bits” of the Journal of Statistics Education; she has also published papers and given professional presentations on the subject of statistics education, with a particular emphasis on statistical literacy (skills for understanding statistics in everyday life and the workplace) and immersive learning environments (environments that promote students’ discovery of ideas on their own). Her passions include fishing, bird watching, and Ohio State Buckeye football (not necessarily in that order).
In the numbers explosion all around us in our modern-day dealings, the buzzword is data, as in, “Do you have any data to support your claim?” “The data supported the original hypothesis that . . .” and “The data bear this out. . . .” But the field of statistics is not just about data. Statistics is the entire process involved in gathering evidence to answer questions about the world, in cases where that evidence happens to be numerical data.
Statistics For Dummies is for everyone who wants to sort through and evaluate the incredible amount of statistical information that comes to them on a daily basis. (You know the stuff: charts, graphs, tables, as well as headlines that talk about the results of the latest poll, survey, experiment, or other scientific study.) This book arms you with the ability to decipher and make important decisions about statistical results, being ever aware of the ways in which people can mislead you with statistics. Get the inside scoop on number-crunching nuances, plus insight into how you can
This down-to-earth reference is chock-full of real examples from real sources that are relevant to your everyday life: from the latest medical breakthroughs, crime studies, and population trends to surveys on Internet dating, cell phone use, and the worst cars of the millennium. Statistics For Dummies departs from traditional statistics texts, references, supplement books, andstudy guides in the following ways:
Chances are, Statistics For Dummies will be your No. 1 resource for discovering how numerical data figures into your corner of the universe.
| Introduction | 1 | |
| About This Book | 1 | |
| Conventions Used in This Book | 2 | |
| Foolish Assumptions | 2 | |
| How This Book Is Organized | 3 | |
| Icons Used in This Book | 5 | |
| Where to Go from Here | 6 | |
| Part I | Vital Statistics about Statistics | 7 |
| Chapter 1 | The Statistics of Everyday Life | 9 |
| Statistics and the Media Blitz: More Questions than Answers? | 9 | |
| Using Statistics at Work | 17 | |
| Chapter 2 | Statistics Gone Wrong | 21 |
| Taking Control: So Many Numbers, So Little Time | 21 | |
| Detecting Errors, Exaggerations, and Just Plain Lies | 22 | |
| Feeling the Impact of Misleading Statistics | 36 | |
| Chapter 3 | Tools of the Trade | 39 |
| Statistics: More than Just Numbers | 39 | |
| Grabbing Some Basic Statistical Jargon | 41 | |
| Part II | Number-Crunching Basics | 59 |
| Chapter 4 | Getting the Picture: Charts and Graphs | 61 |
| Getting Graphic with Statistics | 61 | |
| Getting a Piece of the Pie Chart | 62 | |
| Raising the Bar on Bar Graphs | 72 | |
| Putting Statistics on the Table | 76 | |
| Keeping Pace with Time Charts | 83 | |
| Picturing Data with a Histogram | 86 | |
| Chapter 5 | Means, Medians, and More | 97 |
| Summing Up Data with Statistics | 97 | |
| Summarizing Categorical Data | 98 | |
| Summarizing Numerical Data | 101 | |
| Part III | Determining the Odds | 115 |
| Chapter 6 | What Are the Chances? Understanding Probability | 117 |
| Taking a Chance with Probability | 117 | |
| Gaining the Edge: Probability Basics | 119 | |
| Interpreting Probability | 124 | |
| Avoiding Probability Misconceptions | 124 | |
| Connecting Probability with Statistics | 127 | |
| Chapter 7 | Gambling to Win | 131 |
| Betting on the House: Why Casinos Stay in Business | 131 | |
| Knowing a Little Probability Helps a Lotto | 133 | |
| Part IV | Wading through the Results | 141 |
| Chapter 8 | Measures of Relative Standing | 143 |
| Straightening Out the Bell Curve | 143 | |
| Converting to a Standard Score | 151 | |
| Sizing Up Results Using Percentiles | 156 | |
| Chapter 9 | Caution: Sample Results Vary! | 161 |
| Expecting Sample Results to Vary | 161 | |
| Measuring Variability in Sample Results | 162 | |
| Examining Factors That Influence Variability in Sample Results | 174 | |
| Chapter 10 | Leaving Room for a Margin of Error | 177 |
| Exploring the Importance of That Plus or Minus | 177 | |
| Finding the Margin of Error: A General Formula | 179 | |
| Determining the Impact of Sample Size | 184 | |
| Limiting the Margin of Error | 186 | |
| Part V | Guesstimating with Confidence | 189 |
| Chapter 11 | The Business of Estimation: Interpreting and Evaluating Confidence Intervals | 191 |
| Realizing That Not All Estimates Are Created Equal | 192 | |
| Linking a Statistic to a Parameter | 193 | |
| Making Your Best Guesstimate | 194 | |
| Interpreting Results with Confidence | 194 | |
| Spotting Misleading Confidence Intervals | 195 | |
| Chapter 12 | Calculating Accurate Confidence Intervals | 197 |
| Calculating a Confidence Interval | 197 | |
| Choosing a Confidence Level | 199 | |
| Zooming In on Width | 200 | |
| Factoring In the Sample Size | 201 | |
| Counting On Population Variability | 203 | |
| Chapter 13 | Commonly Used Confidence Intervals: Formulas and Examples | 205 |
| Calculating the Confidence Interval for the Population Mean | 205 | |
| Determining the Confidence Interval for the Population Proportion | 207 | |
| Developing a Confidence Interval for the Difference of Two Means | 208 | |
| Coming Up with the Confidence Interval for the Difference of Two Proportions | 210 | |
| Part VI | Putting a Claim to the (Hypothesis) Test | 213 |
| Chapter 14 | Claims, Tests, and Conclusions | 215 |
| Responding to Claims: Some Do's and Don'ts | 216 | |
| Doing a Hypothesis Test | 219 | |
| Weighing the Evidence and Making Decisions: P-Values | 223 | |
| Knowing That You Could Be Wrong: Errors in Testing | 226 | |
| Walking through a Hypothesis Test: The Big Picture | 229 | |
| Chapter 15 | Commonly Used Hypothesis Tests: Formulas and Examples | 237 |
| Testing One Population Mean | 238 | |
| Testing One Population Proportion | 239 | |
| Comparing Two (Separate) Population Averages | 240 | |
| Testing for an Average Difference (Paired Data) | 242 | |
| Comparing Two Population Proportions | 245 | |
| Part VII | Statistical Studies: The Inside Scoop | 249 |
| Chapter 16 | Polls, Polls, and More Polls | 251 |
| Recognizing the Impact of Polls | 251 | |
| Behind the Scenes: The Ins and Outs of Surveys | 256 | |
| Chapter 17 | Experiments: Medical Breakthroughs or Misleading Results? | 267 |
| Determining What Sets Experiments Apart | 268 | |
| Designing a Good Experiment | 269 | |
| Making Informed Decisions about Experiments | 279 | |
| Chapter 18 | Looking for Links: Correlations and Associations | 281 |
| Picturing the Relationship: Plots and Charts | 282 | |
| Quantifying the Relationship: Correlations and Other Measures | 287 | |
| Explaining the Relationship: Association and Correlation versus Causation | 291 | |
| Making Predictions: Regression and Other Methods | 291 | |
| Chapter 19 | Statistics and Toothpaste: Quality Control | 297 |
| Full-Filling Expectations | 297 | |
| Squeezing Quality out of a Toothpaste Tube | 299 | |
| Part VIII | The Part of Tens | 309 |
| Chapter 20 | Ten Criteria for a Good Survey | 311 |
| The Target Population Is Well Defined | 311 | |
| The Sample Matches the Target Population | 312 | |
| The Sample Is Randomly Selected | 313 | |
| The Sample Size Is Large Enough | 313 | |
| Good Follow-Up Minimizes Non-Response | 314 | |
| The Type of Survey Used Is Appropriate | 315 | |
| The Questions Are Well Worded | 316 | |
| The Survey Is Properly Timed | 317 | |
| The Survey Personnel Are Well Trained | 318 | |
| The Survey Answers the Original Question | 319 | |
| Chapter 21 | Ten Common Statistical Mistakes | 321 |
| Misleading Graphs | 321 | |
| Biased Data | 324 | |
| No Margin of Error | 325 | |
| Non-Random Samples | 326 | |
| Missing Sample Sizes | 327 | |
| Misinterpreted Correlations | 327 | |
| Confounding Variables | 328 | |
| Botched Numbers | 329 | |
| Selectively Reporting Results | 330 | |
| The Almighty Anecdote | 331 | |
| Appendix | Sources | 333 |
| Index | 341 |
In This Chapter
* Encountering statistics in everyday life: what you see and how often you see it
* Discovering how statistics are used in the workplace
Today's society is completely taken over by numbers. Numbers appear
everywhere you look, from billboards telling of the latest abortion statistics,
to sports shows discussing the Las Vegas odds for the upcoming football
game to the evening news, with stories focusing on crime rates, the expected
life span of someone who eats junk food, and the president's approval rating.
On a normal day, you can run into five, ten, or even twenty different statistics
(with even more on Election Night). Just by reading a Sunday newspaper all
the way through, you come across literally hundreds of statistics in reports,
advertisements, and articles covering everything from soup (how much does
an average person consume per year?) to nuts (how many nuts do you have
to eat to increase your IQ?).
The purpose of this chapter is to show you how often statistics appear in
your life and work and how statistics are presented to the general public.
After reading this chapter, you begin to see just howoften the media hits you
with numbers and how important it is to be able to unravel what all those
numbers mean. Because, like it or not, statistics are a big part of your life. So,
if you can't beat 'em, and you don't want to join 'em, you should at least try
to understand 'em.
Statistics and the Media Blitz:
More Questions than Answers?
Open a newspaper and start looking for examples of articles and stories
involving numbers. It doesn't take long before numbers begin to pile up.
Readers are inundated with results of studies, announcements of breakthroughs,
statistical reports, forecasts, projections, charts, graphs, and summaries.
The extent to which statistics occur in the media is mind-boggling.
today's information age. Here are just a few examples from one Sunday
paper's worth of news. While you're reading this, you may find yourself
getting nervous, wondering what you can and can't believe anymore. Relax!
That's what this book is for, helping you sort out the good from the bad information.
(Chapters 2 through 5 give you a great start.)
Probing popcorn problems
The first article I come across that deals with numbers is entitled, "Popcorn
plant faces health probe." The subheading reads "Sick workers say flavoring
chemicals caused lung problems." The article describes how the Centers for
Disease Control (CDC) is expressing concern about a possible link between
exposure to chemicals in microwave popcorn flavorings and some cases of
fixed obstructive lung disease. Eight people from one popcorn plant alone
contracted this lung disease, and four of them were awaiting lung transplants.
According to the article, similar cases were reported at other popcorn
factories. Now, you may be asking, "What about the folks who eat microwave
popcorn?" According to the article, the CDC finds "no reason to believe that
people who eat microwave popcorn have anything to fear." (Stay tuned.)
They say that their next step is to evaluate employees more in-depth, including
surveys to determine health and possible exposures to the said chemicals,
checks of lung capacity, and detailed air samples. The question here is:
How many cases of this lung disease constitute a real pattern, compared to
mere chance or a statistical anomaly? (More about this in Chapter 14.)
Venturing into viruses
The second article I find discusses the most recent cyber attack - a worm-like
virus that has made its way through the Internet, slowing down Web
browsing and e-mail delivery across the world. How many computers were
affected? The experts quoted in the article say that 39,000 computers were
infected, affecting hundreds of thousands of other systems. How did they get
that number? Wouldn't that be a hard number to get hold of? Did they check
each computer out there to see whether it was affected? The fact that this
article was written less than 24 hours after the attack would suggest that this
number is a guess. Then why say 39,000 and not 40,000? To find out more on
how to guesstimate with confidence (and how to evaluate someone else's
numbers) see Chapter 11.
Comprehending crashes
Next in the paper appears an alert about the soaring number of motorcycle
fatalities. Experts say that these fatalities are up more than 50% since 1997,
and no one can figure out why. The statistics tell an interesting story. In 1997,
2,116 motorcyclists were killed; in 2001, the number was 3,181, as reported
by the National Highway Traffic Safety Administration (NHTSA). In the article,
many possible causes for the increased motorcycle death rate are discussed,
including the fact that riders today tend to be older (the average age of motorcyclists
killed in crashes increased from 29.3 years in 1990 to 36.3 years
in 2001).
Bigger bikes are listed as another possibility. The engine size of an average
motorcycle has increased almost 25% - from 769 cubic centimeters in 1990
to 959 cubic centimeters in 2001. Another possibility may be that some states
are weakening their helmet laws. The experts quoted in the article say that a
more comprehensive causation study is needed, but such a study probably
won't be done because it would cost between 2 and 3 million dollars. One
issue that is not addressed in the article is the number of people riding
motorcycles in 2001, compared to the number of riders in1997. More people
on the roads generally means more fatalities, if all the other factors remain
the same. However, along with the article is a graph showing motorcycle
deaths per 100 million vehicle miles traveled in the United States from 1997
to 2001; does that address the issue of more people on the roads? A bar
graph is also included, comparing motorcycle deaths to deaths that occurred
in other types of vehicles. This bar graphs shows that motorcycle deaths
occur at a rate of 34.4 deaths per 100 million vehicle miles traveled, compared
to just 1.7 deaths for the same number of miles traveled in cars. This
article has lots of numbers and statistics, but what does it all mean? The
number and types of statistics can quickly get confusing. Chapter 4 helps you
sort out graphs and charts and the statistics that go along with them.
Mulling malpractice
Further along in the newspaper is a report about a recent medical malpractice
insurance study, which may affect you in terms of the fees your doctor
charges and your ability to get the health care you need. So what's the extent
of the problem? The article indicates that 1 in 5 Georgia doctors has stopped
doing risky procedures (like delivering babies) because of the ever-increasing
malpractice insurance rates in the state. This is described as a "national
epidemic" and a "health crisis" around the country. Some brief details of the
study are included, and the article states that of the 2,200 Georgia doctors
surveyed, 2,800 of them - which they say represents about 18% of those
sampled - were expected to stop providing high risk procedures. Wait a
minute! Can that be right? Out of 2,200 doctors, 2,800 don't perform the procedures,
and that is supposed to represent 18%? That's impossible! You can't
have a bigger number on the top of a fraction, and still have the fraction be
under 100%, right? This is one of many examples of errors in statistics that
are reported in the media. So what's the real percentage? You can only guess.
Chapter 5 nails down the particulars of calculating statistics, so that you can
know what to look for and immediately tell when something's not right.
Belaboring the loss of land
In the same Sunday paper is an article about the extent of land development
and speculation across the country. Given the number of homes likely being
built in your neck of the woods, this is an important issue to get a handle on.
Statistics are given regarding the number of acres of farmland that are being
lost to development each year and also translates those acres to square
miles. To further illustrate how much land is being lost, the area is also listed
in terms of the number of football fields. In this particular example, experts
say that the mid-Ohio area is losing 150,000 acres per year, which is 234
square miles, or 115,385 football fields (including end zones). How do people
come up with these numbers, and how accurate are they? And does it help to
visualize land loss in terms of the corresponding number of football fields?
Scrutinizing schools
The next topic in the paper is school proficiency, specifically whether extra
school sessions are helping students perform better. The article states that
81.3% of students in this particular district who attended extra sessions
passed the writing proficiency test, while only 71.7% of those who didn't participate
in the extra school sessions passed the proficiency test. But is this
enough of a difference to account for the $386,000 price tag per year? And
what's happening in these sessions to account for an improvement? Are students
in these sessions spending more time just preparing for those exams,
rather than learning more about writing in general? And here's the big question:
Were those who participated in these extra sessions student volunteers
who may be more motivated than the average student to try to improve their
test scores? No one knows. Studies like this are going on all the time, and the
only way to know what to believe is to understand what questions to ask, and
to be able to critique the quality of the study. That's all part of statistics! The
good news is, with a few clarifying questions, you can quickly critique statistical
studies and their results. Chapter 17 helps you to do just that.
Studying sports
The sports section is probably the most numerically jam-packed section of
the newspaper. Besides the scores of the last game, the win/lose percentages
for each team in the league, and the relative standing for each team, the specialized
statistics reported in the sports world are so thick that they require
wading boots to get through. For example, the basketball statistics are
broken down by team, by quarter, and even by player. And you need to be a
basketball junkie to interpret all of this, because everything is abbreviated
(with no legend provided if you're out of the loop):
Who needs to know this, besides the players' mothers? Statistics are something
that sports fans can never get enough of and that players can't stand to
hear about. Stats are the substance of water-cooler debates and the fuel for
armchair quarterbacks around the world.
Banking on business news
In the business section of the newspaper, you find statistics about the stock
market. It was a bad week last week, with the stock market going down 455
points; is that decrease a lot or a little? You need to calculate a percentage to
really get a handle on that. In the same business section, you also find reports
on the highest yields nationwide on every kind of CD imaginable. (By the way,
how do they know they're the highest?) You also see reports about loan
rates: rates on 30-year fixed loans, 15-year fixed loans, 1-year adjustable rate
loans, new car loans, used car loans, home equity loans, and loans from your
grandmother (well actually no, but if grandma knew how to read these statistics,
she may consider increasing the cushy rates she lets you have on her
money!). Finally, you see numerous ads for those beloved credit cards - ads
listing the interest rates, the annual fees, and the number of days in the billing
cycle for the credit cards. How do you compare all of the information about
investments, loans, and credit cards in order to make a good decision? What
statistics are most important? The real question is, are the numbers reported
in the paper giving the whole story, or do you need to do more detective
work to get at the truth? Chapter 3 helps you start tearing apart these numbers
and making decisions about them.
Taking in the travel news
You can't even escape the barrage of numbers by escaping to the travel section.
In that section, I find that the most frequently asked question coming in
to the Transportation Security Administration's response center (which
receives about 2,000 telephone calls, 2,500 e-mail messages, and 200 letters
per week on average - would you want to be the one counting all of those?)
is, "Can I carry this on a plane?" where "this" can refer to anything from an
animal to a giant tin of popcorn. (I wouldn't recommend the tin of popcorn.
You have to put it in the overhead compartment horizontally, and because
things shift during flight, the cover will likely open; and when you go to claim
your tin at the end of the flight, you and your seatmates will be showered.
Yes, I saw it happen once.)
This leads to an interesting statistical question: How many operators will
you need at various times of the day to field those calls that will come in?
Estimating the number of anticipated calls is your first step, and being wrong
can cost you money (if you overestimated it) or a lot of bad PR (if you underestimated
it).
Talking sex (and statistics) with Dr. Ruth
On the accent page of the Sunday paper, you can read about Dr. Ruth's latest
research on people's sex lives. She reports that sex doesn't stop at age 60 or
even age 70. That's nice to know, but how did she determine this, and to what
extent are people having sex at these ages? She doesn't say (maybe some statistics
are better left unsaid, huh?). However, Dr. Ruth does recommend that
folks in this age group disregard the surveys that report how many times a
week, month, or year a couple has sex. In her view, this is just people bragging.
She may be right about this. Think about it, if someone conducted a
survey by calling people on the phone asking for a few minutes of their time
to discuss their sex lives, who is going to be the most likely to want to talk
about it? And what are they going to say in response to the question, "How
many times a week do you have sex?" Are they going to report something
that is the honest truth, or are they going to exaggerate a little? Self-reported
surveys can be a real source of bias, and can lead to misleading statistics. So,
don't be too hard on Dr. Ruth (who, by the way, is the author of Sex For
Dummies, 2nd Edition, published by Wiley Publishing, Inc.). How would you
recommend she go about finding out more about this very personal subject?
Sometimes, research is more difficult than it seems.
Continues...
Excerpted from Statistics For Dummies
by Deborah Rumsey
Copyright © 2003 by Deborah Rumsey.
Excerpted by permission.
All rights reserved. No part of this excerpt may be reproduced or reprinted without permission in writing from the publisher.
Excerpts are provided by Dial-A-Book Inc. solely for the personal use of visitors to this web site.
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