Statistical Analysis with Excel For Dummies. Joseph Schmuller
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Название: Statistical Analysis with Excel For Dummies
Автор: Joseph Schmuller
Издательство: John Wiley & Sons Limited
Жанр: Программы
isbn: 9781119844563
isbn:
Know how to use your computer: I don’t spell out the details of pointing, clicking, selecting, and other basic actions.
Have Excel (Microsoft 365 subscription) installed on your machine and can work along with the examples: I don’t walk you through the steps of Excel installation. Incidentally, I work with the 32-bit version — it seems to get the updates more quickly than the 64-bit version does. Excel 2021 should work for most of the examples, but the subscription version receives the latest updates.
Have worked with Excel: I don’t go into the essentials of worksheets and formulas. I do fill you in on a few Excel fundamentals in Chapter 1, however.
If you don't know much about Excel, consider looking into Greg Harvey's excellent Excel books in the For Dummies series.
Icons Used in This Book
As is the case with all For Dummies books, icons appear all over the place. Each one is a little picture in the margin that lets you know something special about the paragraph it sits next to.
Where to Go from Here
You can start the book anywhere, but here are a few hints. Want to learn the foundations of statistics? Turn the page. Introduce yourself to Excel's statistical features? That's Chapter 2. Want to start with graphics? Hit Chapter 3. For anything else, find it in the table of contents or in the index and go for it.
Beyond This Book
In addition to what you’re reading right now, this book comes with a free, access-anywhere Cheat Sheet that will help you quickly use the tools I discuss. To find this Cheat Sheet, visit www.dummies.com and search for Statistical Analysis with Excel For Dummies Cheat Sheet in the Search box. And don’t forget to check out the bonus content on this book’s companion website, at http://www.dummies.com/go/statisticalanalysiswexcelfd5e.
If you’ve read any of the previous editions, welcome back!
If not, it’s nice to meet you.
Part 1
Getting Started with Statistical Analysis with Excel: A Marriage Made in Heaven
IN THIS PART …
Find out about Excel’s statistical capabilities
Explore how to work with populations and samples
Test your hypotheses
Understand errors in decision-making
Determine independent and dependent variables
Chapter 1
Evaluating Data in the Real World
IN THIS CHAPTER
The field of statistics is all about decision-making — decision-making based on groups of numbers. Statisticians constantly ask questions: What do the numbers tell us? What are the trends? What predictions can we make? What conclusions can we draw?
To answer these questions, statisticians have developed an impressive array of analytical tools. These tools help us make sense of the mountains of data that are out there waiting for us to delve into, and to understand the numbers we generate in the course of our own work.
The Statistical (and Related) Notions You Just Have to Know
Because intensive calculation is often part and parcel of the statistician’s tool set, many people have the misconception that statistics is about number crunching. Number crunching is just one small step on the path to sound decisions, however.
By shouldering the number crunching load, software increases your speed of travel down that path. Some software packages are specialized for statistical analysis and contain many of the tools that statisticians use. Although not marketed specifically as a statistical package, Excel provides a number of these tools, which is why I wrote this book.
I just said that number crunching is a small step on the path to sound decisions. The most important part are the concepts statisticians work with, and that’s what I talk about for most of the rest of this chapter.
Samples and populations
On election night, TV commentators routinely predict the outcome of elections before the polls close. Most of the time they’re right. How do they do that?
The trick is to interview a sample of voters right after they cast their ballots. Assuming the voters tell the truth about whom they voted for, and assuming the sample truly represents the population, network analysts use the sample data to generalize to the population of voters.
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