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Data Analytics
Data Analytics

Data Analytics: Master the Art of Data Analytics with Essential Tools and Techniques

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Profile Icon Mercury Learning and Information Profile Icon Christopher Greco
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₱2653.99
eBook Jul 2024 146 pages 1st Edition
eBook
₱2653.99
Arrow left icon
Profile Icon Mercury Learning and Information Profile Icon Christopher Greco
Arrow right icon
₱2653.99
eBook Jul 2024 146 pages 1st Edition
eBook
₱2653.99
eBook
₱2653.99

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Key benefits

  • Comprehensive coverage of data analytics concepts, tools, and applications.
  • Integration of systems engineering, cybersecurity, and project management principles.
  • Practical case studies and real-world examples for hands-on learning.

Description

Data analytics is becoming increasingly important in our daily lives. This book offers a comprehensive view of data analytics skills, starting with a primer on statistics and progressing to the application of these methods. The text includes various formulas and algorithms used in data analytics, which can be applied in any software to achieve desired results. Through numerous demonstrations, it provides clear instruction on how to incorporate data analytics into critical thinking. The book covers a range of methods and techniques, supplemented with case studies specific to project managers, systems engineers, and cybersecurity professionals. Each profession can practice data analytics relevant to their fields. The main objective is to refresh statistical knowledge necessary for building data analytics models and to foster analytical thinking essential across these professions. From introducing statistics and data to reviewing central tendency measures and probability, the book moves to more complex topics like effect size, analysis methods, and data presentation. By the end of the course, readers will be well-versed in data analytics, ready to apply these skills effectively in their respective fields, enhancing decision-making and analytical thinking.

Who is this book for?

Ideal for data analysts, systems engineers, cybersecurity professionals, and project managers, this book requires a basic understanding of statistics and data analysis. It is suitable for those looking to enhance their skills in integrating data analytics with other professional domains.

What you will learn

  • Understand key statistical concepts for data analytics.
  • Differentiate between data types and their applications.
  • Apply probability methods to data analysis.
  • Utilize data analysis tools such as Excel and R.
  • Implement geospatial data analysis techniques.
  • Develop and test hypotheses using advanced analytics methods.

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jul 29, 2024
Length: 146 pages
Edition : 1st
Language : English
ISBN-13 : 9781836643708
Category :
Concepts :

What do you get with eBook?

Product feature icon Instant access to your Digital eBook purchase
Product feature icon Download this book in EPUB and PDF formats
Product feature icon DRM FREE - Read whenever, wherever and however you want
Product feature icon AI Assistant (beta) to help accelerate your learning
OR
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Payment Processing...
tick Completed

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Product Details

Publication date : Jul 29, 2024
Length: 146 pages
Edition : 1st
Language : English
ISBN-13 : 9781836643708
Category :
Concepts :

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Table of Contents

18 Chapters
Acknowledgments Chevron down icon Chevron up icon
1. Introduction To Statistics For Data Analysts Chevron down icon Chevron up icon
2. What Is Data? Chevron down icon Chevron up icon
3. Statistics Review – Measures of The Central Tendency Chevron down icon Chevron up icon
4. Probability Primer Chevron down icon Chevron up icon
5. Occam’s Razor and Data Analytics Chevron down icon Chevron up icon
6. Data Analysis Tools Chevron down icon Chevron up icon
7. Effect Size Chevron down icon Chevron up icon
8. Analysis Process Methods Chevron down icon Chevron up icon
9. Data Analytics Thinking Chevron down icon Chevron up icon
10. Where’s The Data? Chevron down icon Chevron up icon
11. Data Presentation Chevron down icon Chevron up icon
12. Geospatial Data Analytics Chevron down icon Chevron up icon
13. Additional Data Analytics Methods Chevron down icon Chevron up icon
14. Summary Chevron down icon Chevron up icon
15. Case Studies Chevron down icon Chevron up icon
References Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon
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