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This list relates to the time period Academic year 2018-2019 which ended on 31/07/2019
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  1. Text Books 5 items
    1. Data Science for Business - Foster Provost, Tom Fawcett 2013 (electronic resource)

      Book Essential It would be a good idea to have read all of this book by the end of the course.

    2. Data Science for Business - Foster Provost, Tom Fawcett 2013

      Book Essential This is the hard -copy version of the above.

    3. Practical Data Science With R - Nina Zumel, John Mount 2014 (electronic resource)

      Book Essential

    4. Practical Data Science With R - Nina Zumel, John Mount 2014

      Book Essential This is the hard-copy version of the above.

    5. Business Intelligence: A Managerial Perspective on Analytics - Ramesh Sharda, Dursun Delen, Efraim Turban 2014

      Book Essential

  2. General 16 items
    1. Practical Data Science With R - Nina Zumel, John Mount 2014

      Book Essential Chapter 5: Choosing and evaluating models Chapter 10: Documentation and deployment Chapter 11: Producing effectiving presentations

    2. SIGKDD

      Website Further The community for data mining, data science and analytics

    3. IBM Big Data and Analytics - Case Studies - United Kingdom 2015

      Webpage Further Lots of case studies of data analytics in use

    4. Teradata University Network

      Website Further Teradata University Network You will have to register. Then the Library tab has lots of useful resources, including case studies.

    5. Biochar for Environmental Management: Science and Technology - Johannes Lehmann, Stephen Joseph 2009

      Book Further Delete this one later

  3. General R Stuff 1 item
    1. How to Use read.csv() to Import Data in R

      Webpage Recommended Useful information for how to read different types of files into R. Read all of it to get all the required information.

  4. Lecture 1: Introduction to Data Analytics 17 items
    1. Data Science for Business - Foster Provost, Tom Fawcett 2013 (electronic resource)

      Book Essential Chapter 1

    2. Data Science for Business - Foster Provost, Tom Fawcett 2013

      Book Essential Chapter 1

    3. CRISP-DM 1.0: Step-by-Step Data Mining Guide - Pete Chapman 2000

      Document Essential Access here: ftp://ftp.software.ibm.com/software/analytics/spss/support/Modeler/Documentation/14/UserManual/CRISP-DM.pdf

    4. The KDD Process for Extracting Useful Knowledge From Volumes of Data (Knowledge Discovery in Databases) - Usama Fayyad, Gregory Piatetsky - Shapiro, Padhraic Smyth 1996

      Article Recommended A bit complicated to get to this one, but once you get to the page for the journal Communications of the ACM click on the Table of Contents tab and you will then need to scroll down to Volume 39 Issue 11; click on the Table of Contents tab again and you will be able to find the article.

    5. Big Data: The Next Frontier for Innovation, Competition, and Productivity | McKinsey & Company - James Manyika 2011

      Webpage Recommended You can open the full report from this page as a PDF or Kindle version.

    6. Strength in Numbers: How Does Data-Driven Decisionmaking Affect Firm Performance? - Erik Brynjolfsson 2011

      Article Recommended On the SSRN website click on 'Download this paper', then scroll down and choose 'download without registration' on the bottom right

    7. Why Big Data Is on the Rise | Foreign Affairs - Kenneth Neil Cukier, Viktor Mayer-Schoenberger 2013

      Webpage Further

  5. Lecture 2: Understanding and Managing Data 13 items
    1. Data Science for Business - Foster Provost, Tom Fawcett 2013 (electronic resource)

      Book Essential Chapter 2

    2. Data Science for Business - Foster Provost, Tom Fawcett 2013

      Book Essential Chapter 2

    3. Business Intelligence: A Managerial Perspective on Analytics - Ramesh Sharda 2014

      Book Essential Chapter 4 Sections 4.1 to 4.4

    4. Practical Data Science With R - Nina Zumel, John Mount 2014 (electronic resource)

      Book Essential Chapters 1, 2, 3 and 4

    5. Practical Data Science With R - Nina Zumel, John Mount 2014

      Book Essential Chapters 1, 2, 3 and 4

    6. Five Questions to Identify Key Stakeholders - Graham Kenny 2014

      Webpage Recommended You may have to subscribe - but you get a certain number of free articles per month.

    7. Stakeholder Analysis and Management | ExpertBA - Aniket S Sharma 2013

      Webpage Recommended Original link not working. Bookmarked from Web archive.

  6. Lecture 3: Linear Regression 7 items
    1. Practical Data Science With R - Nina Zumel, John Mount 2014 (electronic resource)

      Book Essential Chapter 7 Section 7.1

    2. Practical Data Science With R - Nina Zumel, John Mount 2014

      Book Essential Chapter 7 Section 7.1

    3. Data Science for Business - Foster Provost, Tom Fawcett 2013 (electronic resource)

      Book Suggested for Student Purchase Chapter 2

    4. Data Science for Business - Foster Provost, Tom Fawcett 2013

      Book Essential Chapter 2

    5. Bordeaux Wine Vintage Quality and the Weather - Orley Ashenfelter, David Ashmore, Robert Lalonde

      Webpage Recommended There is a link at the bottom to the data used.

    6. Moneyball: The Art of Winning an Unfair Game - Michael Lewis 2004

      Book Recommended

    7. Moneyball - Bennett Miller, Brad Pitt, Robin Wright, Jonah Hill 2011

      Audio-visual document Further Film to watch - why not make an evening of it with friends on this course!

  7. Lecture 4: Logistic Regression 3 items
    1. Practical Data Science With R - Nina Zumel, John Mount 2014

      Book Essential Chapter 7 section 7.2

    2. Welcome! | Score a Hit!

      Website Recommended Link not working. Bookmarked from web archive.

  8. Lecture 5: Trees 2 items
    1. Practical Data Science With R - Nina Zumel, John Mount 2014

      Book Essential Chapters 6 & 9

    2. Social Pressure and Voter Turnout: Evidence from a Large-Scale Field Experiment - Alan S. Gerber, Donald P. Green, Christopher W. Larimer 2008

      Article Recommended

  9. Lecture 6: Clustering 2 items
    1. Practical Data Science With R - Nina Zumel, John Mount 2014

      Book Essential Chapter 8.1

    2. Data Science for Business - Foster Provost, Tom Fawcett 2013

      Book Essential Chapter 6

  10. Lecture 7: Association Rules 6 items
    1. Data Science for Business - Foster Provost, Tom Fawcett 2013

      Book Essential Chapter 12

    2. Practical Data Science With R - Nina Zumel, John Mount 2014

      Book Essential Chapter 8.2

    3. Mining Association Rules Between Sets of Items in Large Databases - Rakesh Agrawal 1993

      Article Recommended Click on the PDF link at the top left to open the article.

    4. Association Rule Mining - Chengqi Zhang, Shichao Zhang

      Book Further

  11. Lecture 8: Text Analytics 6 items
    1. Data Science for Business - Foster Provost, Tom Fawcett 2013

      Book Essential Chapter 10

  12. Lecture 9: Linear and Integer Programming 1 item
    1. No suggested reading

  13. Lecture 10: Strategic Aspects of Data Analytics 8 items
    1. Data Science for Business - Foster Provost, Tom Fawcett 2013

      Book Essential Chapter 13 & 14

    2. Privacy Regulation and Online Advertising - Avi Goldfarb, Catherine E. Tucker 2011

      Article Recommended

    3. The Dark Side of Customer Analytics - Thomas Davenport 2007

      Article Further Fictional Case Study

  14. Data Sets 5 items
    Possible sources of data for assignment
    1. Webinars and Videos On Demand

      Webpage Further RStudio webinars and videos are presented on a variety of subjects - there are some really interesting things here some of which cover techniques which go way beyond what I teach in the course but may be of use to you if you want to go "off piste".

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