Data Analysis for Decision Making

University College Dublin

Course Description

  • Course Name

    Data Analysis for Decision Making

  • Host University

    University College Dublin

  • Location

    Dublin, Ireland

  • Area of Study

    Information Studies, Statistics

  • Language Level

    Taught In English

  • Course Level Recommendations


    ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.

    Hours & Credits

  • ECTS Credits

  • Recommended U.S. Semester Credits
  • Recommended U.S. Quarter Units
  • Overview

    In the era of "Big Data", there is a challenge to turn data into insight. Data Analysis is the application of statistical techniques to describe and explore a set of data with the objective of highlighting useful information. Data Analysis is used to support evidence-based decision making.
    This module is a foundation in data analysis for all business students and aims to serve the needs of subsequent courses in areas such as marketing, finance, accounting and business analytics. The three main areas introduced in this course are: 
    1/ Data Analysis using Excel: how to use a spreadsheet tool such as Excel. For example, to create a budget for a small business such as a coffee shop or to analyse data gathered from the coffee shop. 
    2/ Quantitative Analysis and Descriptive Statistics: how to gather and interpret large volumes of data in order to describe the information in concise and useful ways. For example, what is the average spend of a sample of customers in a coffee shop? 
    3/ Probability and Inferential Statistics: how to infer population parameters from sample statistics. For example, estimate how much is likely to be spent in the coffee shop in total. 
    This module is delivered using blended learning. Learning resources are available on Blackboard and participants engage in active learning exercises during face-to-face contact time.

Course Disclaimer

Courses and course hours of instruction are subject to change.

Credits earned vary according to the policies of the students' home institutions. According to ISA policy and possible visa requirements, students must maintain full-time enrollment status, as determined by their home institutions, for the duration of the program.

ECTS (European Credit Transfer and Accumulation System) credits are converted to semester credits/quarter units differently among U.S. universities. Students should confirm the conversion scale used at their home university when determining credit transfer.

Please reference fall and spring course lists as not all courses are taught during both semesters.

Please note that some courses with locals have recommended prerequisite courses. It is the student's responsibility to consult any recommended prerequisites prior to enrolling in their course.


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