Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python
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Description
📈 Elevate your data game with stats that actually make sense!
- DUAL LANGUAGE POWER - Hands-on examples in both Python and R to boost your coding versatility.
- BIAS BUSTING TECHNIQUES - Learn random sampling and experimental design to ensure data integrity.
- BRIDGING THEORY PRACTICE - Master essential stats concepts tailored for data science workflows.
- FROM BASICS TO MACHINE LEARNING - Explore regression, classification, and unsupervised learning in one guide.
- QUICK REFERENCE LASTING IMPACT - Concise, readable format perfect for busy professionals leveling up fast.
Practical Statistics for Data Scientists (2nd edition) is a 350-page paperback by O'Reilly Media that delivers over 50 essential statistical concepts with practical Python and R examples. Designed for data scientists with some stats background, it bridges the gap between theory and real-world data science applications, covering exploratory data analysis, sampling, experimental design, regression, classification, and machine learning methods. Highly rated for its approachable style and concise code, it’s a must-have quick reference for professionals aiming to sharpen their statistical toolkit.
Specifications
| Best Sellers Rank | #35,600 in Books ( See Top 100 in Books ) #17 in Mathematical Analysis #43 in Databases & Big Data #46 in Computer Software |
| Customer reviews | 4.5 4.5 out of 5 stars (884) |
| Dimensions | 17.78 x 2.29 x 23.11 cm |
| Edition | 2nd |
| ISBN-10 | 149207294X |
| ISBN-13 | 978-1492072942 |
| Item weight | 612 g |
| Language | English |
| Print length | 360 pages |
| Publication date | 24 June 2020 |
| Publisher | O′Reilly |
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