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From the Back Cover Learn to: Collect, clean, and interpret data Effectively communicate data analysis Make good predictions Big data making you dizzy? Relax—here′s what it′s all about Big data figures into everything from weather forecasting to political polling. Don′t let it give you a big headache; use this friendly book to learn about it in manageable, bite–size chunks. You′ll get a handle on the statistical methods used when working with big data, applications for it, ways to organize and check data, and a whole lot more. Solving the big mystery—find out what big data is, characteristics that define it, how it′s used, and what it makes possible How to handle it — explore statistical techniques used with big data, including probability distributions, regression analysis, time series analysis, and forecasting techniques Getting graphical — learn how big data can be analyzed with graphical techniques and how to identify valid, useful, and understandable patterns in data A variable approach — examine key univariate and multivariate statistical techniques for analyzing data Thinking ahead — discover techniques for forecasting the future values of a dataset There′s a tool for that — learn about the best software packages and programming tools for analyzing statistical data Open the book and find: Ways to extract previously unknown information from a database Tips for data collection and cleaning Techniques for analyzing time series data How to check data for missing information What to do with outliers in a dataset Some surprising uses for big data An overview of modeling techniques About the Author Alan Anderson, PhD, is a professor of economics and finance at Fordham University and New York University. He′s a veteran economist, risk manager, and fixed income analyst. David Semmelroth is an experienced data analyst, trainer, and statistics instructor who consults on customer databases and database marketing.
V**Y
Rumsey is much more useful for those who like me are getting into the ...
This book is big on formulas, but does not have enough practical examples and exercises to get the hand on statistics. The "Statistics Essentials for Dummies" by D. Rumsey is much more useful for those who like me are getting into the world of statistics.
A**R
not specific for big data
It is just a book on traditional statistics and there is hardly any link with the big data phenomenon
V**L
Meh. Not great.
Not a great book. It starts off well enough with some basic information about what big data is and how it's used (mostly chapter 3), but is essentially a book of recipes for statistical tests. The connections to big data are too limited or not even there. I can find recipes anywhere, and they don't help me see how these tests are used on big data. This is especially a problem because too many examples re-hash the same small points about the stock market.The book needs at least one specific big example. Start by describing a publicly available data file (with screen shots). Then give me specifics on preliminary analysis on it (writing "make a histogram and do a chi-square test" does not achieve this goal). How do I pick a method to use for analyzing this dataset? Then go through a couple ways to do that. Repeat with another dataset. Instead, the book just tells you the formula for different tests and makes vague statements about why you'd use one. I can get that from any statistics book.Added: the book is also missing information in places. Example: page 57 says "there are four types of data." Page 58 supposedly describes them, but it stops at two types (leaves out interval data and ratio data).
Trustpilot
3 days ago
2 weeks ago