Khan, Arshad

Business Intelligence and Data Analysis in the Age of AI

Campesato, Oswald

Beginning Python 3 with Claude 3

Fortino, Andres

Case Studies in Excel, R, and ChatGPT

Data Analysis for Business Decisions

Zherlitsyn, Dmytro

Financial Data Analysis Using Python

A Prompt-based Exploration of LLMs

Large Language Models for Developers

Beginning Python 3 with Grok 2

Herman, Erik

Using Analytics and Case Studies

Data Science for Decision Makers

Goralski, Walter

Understanding AI, IoT, 6G and The Infrastructure Revolution

Erik, Herman L.

Theory, Applications and Ethics

AI Revealed

CAMPESATO, OSWALD

CSS3 and SVG with Meta AI

R • Excel • KNIME • OpenOffice

Data Science Tools

Frontmatter

CONTENTS

Preface

Acknowledgments

Notes on Permissions

Chapter 1: First Steps

Chapter 2: Importing Data

Chapter 3: Statistical Tests

Chapter 4: More Statistical Tests

Chapter 5: Statistical Methods for Specific Tools

Chapter 6: Summary

Chapter 7: Supplemental Information

Index

Greco, Christopher

In the world of data science there are myriad tools available to analyze data. This book describes some of the popular software application tools along with the processes for downloading and using them in the most optimum fashion. The content includes data analysis using Microsoft Excel, KNIME, R, and OpenOffice (Spreadsheet). Each of these tools will be used to apply statistical concepts including confidence intervals, normal distribution, T-Tests, linear regression, histograms, and geographic analysis using real data from Federal Government sources.

In the world of data science there are myriad tools available to analyze data. This book describes some of the popular software application tools along with...

Format

Data Science Tools

R • Excel • KNIME • OpenOffice

Christopher Greco

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