Data Analysis for Decision Making

Data Analysis for Decision Making

Closed
Course
en
English
56 h
This content is rated 5 out of 5
Source
  • From www.edx.org
More info
  • 7 Sequences
  • Advanced Level
  • Starts on October 3, 2021
  • Ends on December 12, 2021

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Course details

Syllabus

  • How to separate randomness from truly correlated and potentially causative variables.
  • How to determine if certain variables (e.g., your firm’s spending on advertising or sales personnel) are related to or are driving other variables (e.g., your sales)
  • How to generate forecasts of future demand, and how trends, seasonality, and extreme events, along with random noise impact our ability to predict the future
  • How to effectively visualize these relationships using the latest in data visualization tools

Prerequisite

None.

Instructors

Margrét Bjarnadóttir
Professor of Decision, Operations & Information Technologies
University of Maryland

P.K. Kannan
Professor of Marketing, Dean’s Chair in Marketing Science, Assoc. Dean
University of Maryland

Lingling Zhang
Assistant Professor of Marketing
University of Maryland

Kislaya Prasad
Research Professor, Academic Director, Center for Global Business
University of Maryland

Editor

The University of Maryland is the state's flagship university and one of the nation's leading public research universities. A world leader in research, entrepreneurship and innovation, the university is home to more than 37,000 students, 9,000 faculty and staff, and 250 academic programs. 

Its faculty includes three Nobel laureates, three Pulitzer Prize winners, 47 members of national academies and a large number of Fulbright scholars. The institution has an operating budget of $1.8 billion, raises $500 million a year in external research funding and recently completed a $1 billion fundraising campaign.

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