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Business Analytics:�Overview

Ken Abbott

(917) 714-4810

abbottkc@gmail.com

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Things you will learn:

  • Research methods
    • Where to look
    • How to look
  • Exploratory Data Analysis
  • Key resource available to you
    • Bloomberg
    • Factset
    • S&P Capital IQ
    • US Government sources
    • Worldbank/IMF sources
  • Microsoft Excel
  • Microsoft PowerPoint
  • Basic statistics
    • Distributions
    • Linear regression
    • Correlation
  • Analytical Writing
  • Presentation Skills
  • Fintech Basics

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What I want you to take away from this course:

  1. Don’t be scared of big datasets.
  2. If you can view the data, you can capture the data.
  3. Graphics are key to understanding and communicating concepts.
  4. Graphics require practice, but it’s important to know what you can do.
  5. You don’t have to be a quant to do regression.
  6. Regression can be done via several very different tools.
  7. Taxonomy and organization are key.
  8. There are many great data sources out there, but they can be complex.
  9. Writing a long paper can be easier than you think it might be.
  10. Clear business writing is crucial to advancement.
  11. Presentation skills are KEY and easy to learn
  12. Fintech is important

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Key Topics

  • Learning how to write
  • Write for business purposes
  • Writing papers of different lengths
  • Gathering data
  • Integrating graphics

  • Manipulating text & graphics
  • Expository vs analytical papers
  • Presentation
  • Common problems
  • Elements of a paper/project

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Elements of a paper / project

  • Identification / Problem Statement Week 1
  • Data Analysis I: Getting the Data Week 2
  • Literature review Week 3
  • Design and proposal Week 4
  • Data Analysis II: Modeling the data Week 5-8
  • Review Week 9
  • Draft Week 10
  • Final Version Week 11
  • Presentation Week 12

WorldQuant University