MIS10090 Data Analysis for Decision Mak

Academic Year 2019/2020

In the era of Analytics and "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. 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? 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 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 Brightspace and participants engage in active learning exercises during face-to-face contact time.

Show/hide contentOpenClose All

Curricular information is subject to change

Learning Outcomes:

On completion of this module students should be able to:
- Calculate, analyse and present useful statistical measurements from large-scale data sets;
- Use common probability distributions and statistical functions, and prepare spreadsheet models to store, manipulate and analyse quantitative data using these distributions;
- Create and interpret inferential statistical statements about population parameters;
- Interpret the results of data analyses with a view to informing decision making.

Indicative Module Content:

Main topics:
- Calculation, analysis and presentation of useful statistical measurements from large-scale data sets.
- Analysis of quantitative data using common probability distributions and statistical functions.
- Creation and interpretation of inferential statistical statements about population parameters.
- Interpretation of the results of data analyses with a view to informing decision making.

Student Effort Type Hours
Lectures

24

Tutorial

12

Specified Learning Activities

20

Autonomous Student Learning

70

Total

126

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Equivalents:
Quantitative Analysis for Busi (MIS10010), Data Analysis Decision Makers (SBUS10050)

 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Continuous Assessment: Team assignment Week 9 n/a Graded No

25

Examination: Written Exam 2 hour End of Trimester Exam No Graded No

75


Carry forward of passed components
Yes
 
Resit In Terminal Exam
Autumn Yes - 2 Hour
Feedback Strategy/Strategies

• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

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
Name Role
Mr Fabian Ofurum Tutor
Spring
     
Lecture Offering 2 Week(s) - Spring: All Weeks Mon 11:00 - 12:50
Lecture Offering 3 Week(s) - Spring: All Weeks Mon 16:00 - 17:50
Small Group Offering 1 Week(s) - Spring: All Weeks Mon 14:00 - 14:50
Small Group Offering 2 Week(s) - Spring: All Weeks Mon 15:00 - 15:50
Small Group Offering 3 Week(s) - Spring: All Weeks Mon 16:00 - 16:50
Small Group Offering 4 Week(s) - Spring: All Weeks Mon 17:00 - 17:50
Small Group Offering 5 Week(s) - Spring: All Weeks Tues 09:00 - 09:50
Small Group Offering 6 Week(s) - Spring: All Weeks Tues 10:00 - 10:50
Small Group Offering 7 Week(s) - Spring: All Weeks Tues 11:00 - 11:50
Small Group Offering 8 Week(s) - Spring: All Weeks Thurs 09:00 - 09:50
Small Group Offering 9 Week(s) - Spring: All Weeks Thurs 10:00 - 10:50
Small Group Offering 10 Week(s) - Spring: All Weeks Thurs 11:00 - 11:50
Small Group Offering 11 Week(s) - Spring: All Weeks Thurs 17:00 - 17:50
Spring
     

Discover our Rankings and Accreditations