| Description |
1 online resource (1 volume) : illustrations |
| Bibliography |
Includes bibliographical references and index. |
| Summary |
Haider offers informative, jargon-free coverage of basic theory and technique, backed with plenty of vivid examples and hands-on practice opportunities. Everything is software and platform agnostic, so you can learn data science whether you work with R, Stata, SPSS, or SAS. She teaches a crucial skillset most data science books ignore: how to tell powerful stories using graphics and tables. Every chapter is built around real research challenges, so you'll always know why you're doing what you're doing. You'll master data science by answering fascinating questions. For each problem, you'll walk through defining your question and the answers you'll need; exploring how others have approached similar challenges; selecting your data and methods; generating your statistics; organizing your report; and telling your story. -- Edited summary from book. |
| Subject |
Data mining.
|
|
Business enterprises -- Data processing.
|
|
Data Mining |
|
Exploration de données (Informatique) |
|
Entreprises -- Informatique. |
|
Business enterprises -- Data processing |
|
Data mining |
| Other Form: |
Print version: Haider, Murtaza. Getting started with data science. Boston : IBM Press, Pearson, [2016] (DLC) 2015947691 |
| ISBN |
9780133991246 |
|
0133991245 |
|
9780133991239 |
|
0133991237 |
|
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