# Statistical Analysis with R For Dummies 1st Edition

| |**Pdf Book Name**: Statistical Analysis with R For Dummies 1st Edition

**Author**: Joseph Schmuller

**Publisher**: Wiley

**ISBN-10, 13**: 9781119337065,978-1119337065

**Year**: 2017

**Pages**: 464 pages

**Language**: English

**File size**: 11 MB

**File format**: PDF,EPUB

## Statistical Analysis with R For Dummies 1st Edition Pdf Book Description:

Statistics? That’s all about crunching numbers into arcane-looking formulas, right? Not really. Statistics, first and foremost, is about decision-making. Some number crunching is involved, of course, but the primary goal is to use numbers to make decisions. Statisticians look at data and wonder what the numbers are saying. What kinds of trends are in the data? What kinds of predictions are possible? What conclusions can we make? To make sense of data and answer these questions, statisticians have developed a wide variety of analytical tools. About the number-crunching part: If you had to do it via pencil and paper (or with the aid of a pocket calculator), you’d soon get discouraged with the amount of computation involved and the errors that might creep in. Software like R helps you crunch the data and compute the numbers. As a bonus, R can also help you comprehend statistical concepts. Developed specifically for statistical analysis, R is a computer language that implements many of the analytical tools statisticians have developed for decision making. I wrote this book to show how to use these tools in your work.

The analytical tools that that R provides are based on statistical concepts I help you explore in the remainder of this chapter. As you’ll see, these concepts are based on common sense. If you watch TV on election night, you know that one of the main events is the prediction of the outcome immediately after the polls close (and before all the votes are counted). How is it that pundits almost always get it right? The idea is to talk to a sample of voters right after they vote. If they’re truthful about how they marked their ballots, and if the sample is representative of the population of voters, analysts can use the sample data to draw conclusions about the population. That, in a nutshell, is what statistics is all about using the data from samples to draw conclusions about populations. Here’s another example. Imagine that your job is to find the average height of 10 year-old children in the United States. Because you probably wouldn’t have the time or the resources to measure every child, you’d measure the heights of a representative sample. Then you’d average those heights and use that average as the estimate of the population average.

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