Title
Data Analysis With R: Load, Wrangle, And Analyze Your Data Using The World'S Most Powerful Statistical Programming Language
Delivery time: 8-12 business days (International)
Key Features Load, Manipulate And Analyze Data From Different Sources Gain A Deeper Understanding Of Fundamentals Of Applied Statistics A Practical Guide To Performing Data Analysis In Practice Book Descriptionfrequently The Tool Of Choice For Academics, R Has Spread Deep Into The Private Sector And Can Be Found In The Production Pipelines At Some Of The Most Advanced And Successful Enterprises. The Power And Domainspecificity Of R Allows The User To Express Complex Analytics Easily, Quickly, And Succinctly. With Over 7,000 User Contributed Packages, It'S Easy To Find Support For The Latest And Greatest Algorithms And Techniques.Starting With The Basics Of R And Statistical Reasoning, Data Analysis With R Dives Into Advanced Predictive Analytics, Showing How To Apply Those Techniques To Realworld Data Though With Realworld Examples.Packed With Engaging Problems And Exercises, This Book Begins With A Review Of R And Its Syntax. From There, Get To Grips With The Fundamentals Of Applied Statistics And Build On This Knowledge To Perform Sophisticated And Powerful Analytics. Solve The Difficulties Relating To Performing Data Analysis In Practice And Find Solutions To Working With Messy Data , Large Data, Communicating Results, And Facilitating Reproducibility.This Book Is Engineered To Be An Invaluable Resource Through Many Stages Of Anyone'S Career As A Data Analyst.What You Will Learn Navigate The R Environment Describe And Visualize The Behavior Of Data And Relationships Between Data Gain A Thorough Understanding Of Statistical Reasoning And Sampling Employ Hypothesis Tests To Draw Inferences From Your Data Learn Bayesian Methods For Estimating Parameters Perform Regression To Predict Continuous Variables Apply Powerful Classification Methods To Predict Categorical Data Handle Missing Data Gracefully Using Multiple Imputation Identify And Manage Problematic Data Points Employ Parallelization And Rcpp To Scale Your Analyses To Larger Data Put Best Practices Into Effect To Make Your Job Easier And Facilitate Reproducibility Table Of Contents Refresher The Shape Of Data Describing Relationships Probability Using Data To Reason About The World Testing Hypotheses Bayesian Methods Predicting Continuous Variables Predicting Categorical Variables Sources Of Data Dealing With Messy Data Dealing With Large Data Reproducibility And Best Practices
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Shipping
We ship your order within 2–3 business days for USA deliveries and 5–8 business days for international shipments. Once your package has been dispatched from our warehouse, you'll receive an email confirmation with a tracking number, allowing you to track the status of your delivery.
Returns
To facilitate a smooth return process, a Return Authorization (RA) Number is required for all returns. Returns without a valid RA number will be declined and may incur additional fees. You can request an RA number within 15 days of the original delivery date. For more details, please refer to our Return & Refund Policy page.
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Warranty
We provide a 2-year limited warranty, from the date of purchase for all our products.
If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.
This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).
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Frequently Asked Questions
- Q: What is the main focus of 'Data Analysis With R'? A: The book focuses on teaching readers how to load, wrangle, and analyze data using R, one of the most powerful statistical programming languages, with a strong emphasis on applied statistics.
- Q: Who is the author of this book? A: The author of 'Data Analysis With R' is Tony Fischetti.
- Q: What topics are covered in this book? A: The book covers a range of topics including data manipulation, statistical reasoning, predictive analytics, hypothesis testing, Bayesian methods, and handling messy data.
- Q: Is this book suitable for beginners? A: Yes, the book starts with the basics of R and statistical reasoning, making it suitable for beginners while also providing advanced concepts for more experienced users.
- Q: How many pages does 'Data Analysis With R' have? A: The book has a total of 363 pages.
- Q: What type of binding does this book have? A: This book is available in paperback binding.
- Q: When was 'Data Analysis With R' published? A: The book was published on December 31, 2015.
- Q: What can I learn from this book? A: You can learn to navigate the R environment, visualize data, perform hypothesis tests, apply regression and classification methods, and manage large and messy datasets.
- Q: Does this book include practical examples? A: Yes, the book includes real-world examples and engaging problems to help readers apply the techniques learned.
- Q: Is this book helpful for data analysis careers? A: Absolutely, it is designed to be a valuable resource throughout various stages of a data analyst's career.