MIS2001H Data Analysis for Decision Makers

Academic Year 2023/2024

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. This module is a foundation in data analysis for business students and aims to serve the needs of subsequent courses in areas such as marketing, finance, accounting and business analytics.

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.

Probability and inferential statistics: how to infer population parameters from sample statistics. For example, how much is likely to be spent in the coffee shop in total.

Introduction to predictive modelling: how to estimate future values based on an extension of current trends. For example, estimate sales next year based on sales in the last 10 years.

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Curricular information is subject to change

Learning Outcomes:

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

Student Effort Type Hours
Lectures

20

Specified Learning Activities

85

Autonomous Student Learning

125

Total

230

Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Equivalents:
Management Research Project (BMGT2003H)


 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Examination: Examination 2 hour End of Trimester Exam No Graded No

60

Continuous Assessment: Cont. Assessment and MCQ Varies over the Trimester n/a Graded No

40


Carry forward of passed components
No
 
Resit In Terminal Exam
Spring Yes - 2 Hour
Feedback Strategy/Strategies

• Group/class feedback, post-assessment

How will my Feedback be Delivered?

General feedback is provided to students on all their submitted assessment components.

Name Role
Dr Christina Burke Tutor
Mr Neil Caraher Tutor
Assoc Professor Paula Carroll Tutor
Wincey Cheung Tutor
Ms Michele Connolly Doran Tutor
Mrs Edna Eugenia Da Silva Tutor
Patrick Ng Tutor
Michael Wong Tutor

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