Statistics and data visualisation with python

By:

Rogel-Salazar, Jesus

Material type: Text

TextSeries: Chapman & Hall/CRC Press the python seriesPublication details: CRC Press Oxon 2023Description: 515 pISBN:

9780367744519

Subject(s):

DDC classification:

519.5 ROG

Summary: This book aims to bridge the gap between statistics for graduates and business practitioners, providing a refresher for those who have taken statistics courses but haven't used them in their daily work. It also caters to those new to Python statistical work. Statistics and Data Visualisation with Python aims to build statistical knowledge by understanding inferential statistics and formulating hypotheses for applications in statistical analysis, business analytics, machine learning, and applied machine learning. It starts with Python programming and data analysis basics to provide a solid foundation in statistical methods and hypothesis testing.

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode	Item holds
Book	Jammu General Stacks	Non-fiction	519.5 ROG (Browse shelf(Opens below))	Available		IIMJ-9090

Total holds: 0

1. Data, Stats and Stories - An Introduction 2. Python Programming Primer 3. Snakes, Bears & Other Numerical Beasts: NumPy, SciPy & Pandas 4. The Measure of All Things - Statistics 5. Definitely Maybe: Probability and Distributions 6. Alluring Arguments and Ugly Facts - Statistical Modelling and Hypothesis Testing 7. Delightful Details - Data Visualisation 8. Dazzling Data Designs - Creating Charts

This book aims to bridge the gap between statistics for graduates and business practitioners, providing a refresher for those who have taken statistics courses but haven't used them in their daily work. It also caters to those new to Python statistical work. Statistics and Data Visualisation with Python aims to build statistical knowledge by understanding inferential statistics and formulating hypotheses for applications in statistical analysis, business analytics, machine learning, and applied machine learning. It starts with Python programming and data analysis basics to provide a solid foundation in statistical methods and hypothesis testing.

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