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Data Analysis with R

You're reading from  Data Analysis with R

Product type Book
Published in Dec 2015
Publisher
ISBN-13 9781785288142
Pages 388 pages
Edition 1st Edition
Languages
Toc

Table of Contents (20) Chapters close

Data Analysis with R
Credits
About the Author
About the Reviewer
www.PacktPub.com
Preface
1. RefresheR 2. The Shape of Data 3. Describing Relationships 4. Probability 5. Using Data to Reason About the World 6. Testing Hypotheses 7. Bayesian Methods 8. Predicting Continuous Variables 9. Predicting Categorical Variables 10. Sources of Data 11. Dealing with Messy Data 12. Dealing with Large Data 13. Reproducibility and Best Practices Index

Wait to optimize


Prominent computer scientist and mathematician Donald Knuth famously stated:

Premature optimization is the root of all evil.

I, personally, hold that money is the root of all evil, but premature optimization is definitely up there!

Why is premature optimization so evil? Well, there are a few reasons. First, programmers can sometimes be pretty bad at identifying what the bottleneck of a program—the routine(s) that have the slowest throughput—is and optimize the wrong parts of a program. Identification of bottlenecks can most accurately be performed by profiling your code after it's been completed in an un-optimized form.

Secondly, clever tricks and shortcuts for speeding up code often introduce subtle bugs and unexpected behavior. Now, the speedup of the code—if there is any!—must be taken in context with the time it took to complete the bug-finding-and-fixing expedition; occasionally, a net negative amount of time has been saved when all is said and done.

Lastly, since premature...

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