Data Science Tools

Data Science Tools

R • Excel • KNIME • OpenOffice

Christopher Greco
Paperback
May 2020
9781683925835
More details
  • Publisher
    Mercury Learning & Information
  • Published
    18th May
  • ISBN 9781683925835
  • Language English
  • Pages 206 pp.
  • Size 7" x 9"
$49.95
Add to Cart
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May 2020
9781683925811
More details
  • Publisher
    Mercury Learning & Information
  • Published
    6th May
  • ISBN 9781683925811
  • Language English
  • Pages 206 pp.
  • Size 7" x 9"
$149.95
E-Book (ePub)
May 2020
9781683925828
More details
  • Publisher
    Mercury Learning & Information
  • Published
    14th May
  • ISBN 9781683925828
  • Language English
  • Pages 206 pp.
  • Size 7" x 9"
$39.95
Add to Cart

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.

Features:

  • Analyzes data using popular applications such as Excel, R, KNIME, and OpenOffice
  • Covers statistical concepts including confidence intervals, normal distribution, T-Tests, linear regression, histograms, and geographic analysis
  • Capstone exercises analyze data using the different software packages

"Data Science Tools covers Excel, OpenOffice, KIME and R, and examines how statistical concept are analyzed, translated, and surveyed. It uses data from Federal sources and reviews basic statistical concepts, from distribution and histrograms to various forms of analysis and representation. The contrast between the different software approaches and uses will especially interest students looking to understand the different software systems and how they approach data representation and analysis."

- Midwest Book Review

1: First Steps
2: Importing Data
3: Statistical Tests
4: More Statistical Tests
5: Statistical Methods for Specific Tools
6: Summary
7: Supplemental Information
Index

Christopher Greco

Christopher Greco is a COMPTIA Certified Technical Trainer and Microsoft Certified Systems Engineer with numerous years of industry experience in the areas of data analysis, cybersecurity, and IT instruction and training. He currently teaches data analytics as an independent contractor for a major training company located near Washington, DC.