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MIS10090

Academic Year 2024/2025

Data Analysis for Decision Makers (MIS10090)

Subject:
Management Information Systems
College:
Business
School:
Business
Level:
1 (Introductory)
Credits:
5
Module Coordinator:
Assoc Professor Sean McGarraghy
Trimester:
Spring
Mode of Delivery:
On Campus
Internship Module:
No
How will I be graded?
Letter grades

Curricular information is subject to change.

In the era of Analytics, 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 and so is a core part of Business Analytics.

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. 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. Practical exercises will use a spreadsheet tool such as Excel.
2. Probability and Distributions: discrete and continuous with examples from the real world
3. Inferential Statistics: how to infer population parameters from sample statistics. For example, estimate the average of a population, giving a confidence interval (margin of error).

This module is delivered using blended learning. Learning resources, including quizzes, are available on Brightspace and students engage in active learning exercises during face-to-face contact time.

About this Module

Learning Outcomes:

On completion of this module students should be able to:
- Discuss and use the main concepts and approaches of descriptive statistics;
- Calculate, analyse, visualise and present useful statistical measurements from large-scale data sets;
- Use common probability distributions and statistical functions;
- Devise, test and interpret inferential statistical statements about population parameters;
- Prepare spreadsheet models to store, manipulate and analyse quantitative data;
- Interpret the results of data analyses with a view to informing decision making.

Indicative Module Content:

Main topics:
- The role of data analysis in business and decision making
- Data Gathering, Visualisation and Presentation
- Descriptive Statistics
- Basic Probability
- Conditional Probability and Bayes's Theorem
- Probability Distributions and Random Variables
- Discrete Probability Distributions
- Continuous Probability Distributions
- The Normal Distribution
- Sampling
- Confidence Intervals
- Hypothesis Testing

Student Effort Hours:
Student Effort Type Hours
Lectures

24
Tutorial

12
Specified Learning Activities

20
Autonomous Student Learning

70
Total

126

Approaches to Teaching and Learning:
Lectures and tutorials are face-to-face. The learning approach incorporates:
- pre-lecture reading and reflection on online Brightspace materials;
- lectures and tutorials;
- reflective learning;
- active/task-based learning: online quizzes and continuous assessment.

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Incompatibles:
ECON10030 - Intro Quantitative Economics, ECON20040 - Statistics for Economists

Equivalents:
Quantitative Analysis for Busi (MIS10010), Data Analysis Decision Makers (SBUS10050)


 

Assessment Strategy
Description Timing Component Scale Must Pass Component % of Final Grade In Module Component Repeat Offered
Quizzes/Short Exercises: Each Friday except Good Friday: a short Brightspace quiz to assess the students' understanding of the topics covered in that week's lecture and tutorial. Each is worth 3%, total 30% of grade. Week 2, Week 3, Week 4, Week 5, Week 6, Week 7, Week 8, Week 9, Week 10, Week 12 Standard conversion grade scale 40% No
30
 No
Exam (In-person): Main exam held during the exam period in early May. End of trimester
Duration:
2 hr(s)
 Standard conversion grade scale 40% No
70
 No

Carry forward of passed components
Yes
 

Resit In Terminal Exam
Autumn Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 

Feedback Strategy/Strategies

• Group/class feedback, post-assessment
• Online automated feedback

How will my Feedback be Delivered?

There will be 10 weekly quizzes and once each is finished each student will be able to view their results and see where they need to improve. Also the lecturers will send a general email summarising the overall performance in each week's quiz and highlighting common themes.

Recommended but not compulsory:
Lind, D. A., W. G. Marchal and S. A. Wathen. (2012). Basic Statistics for Business and Economics. McGraw-Hill

Alternative for background reading:
Berenson, M., D. Levine and T. Krehbiel. (2012). Basic Business Statistics: Concepts and Applications. Pearson Prentice Hall

Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
Spring Lecture Offering 2 Week(s) - 20, 21, 23, 24, 25, 26, 29, 31, 32, 33 Mon 13:00 - 14:50
Spring Lecture Offering 3 Week(s) - 20, 21, 23, 24, 25, 26, 29, 31, 32, 33 Mon 16:00 - 17:50
Spring Small Group Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Tues 13:00 - 13:50
Spring Small Group Offering 2 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Tues 14:00 - 14:50
Spring Small Group Offering 3 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Thurs 13:00 - 13:50
Spring Small Group Offering 4 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Thurs 14:00 - 14:50
Spring Small Group Offering 5 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Tues 09:00 - 09:50
Spring Small Group Offering 6 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Tues 10:00 - 10:50
Spring Small Group Offering 7 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Tues 11:00 - 11:50
Spring Small Group Offering 8 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Thurs 09:00 - 09:50
Spring Small Group Offering 9 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Thurs 10:00 - 10:50
Spring Small Group Offering 10 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Thurs 11:00 - 11:50
Spring Small Group Offering 11 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Thurs 15:00 - 15:50
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