Modules

Core Module Information
Module title: Data Analysis
SCQF level: 08:
SCQF credit value: 20.00
ECTS credit value: 10
Module code: FIN08108
Module leader: Carles Ibanez
School The Business School
Subject area group: Accounting and Finance
Prerequisites

There are no pre-requisites for this module to be added
Description of module content:

In this module you will learn how to analyse empirical data and how to interpret statistical outputs. You will learn how to compute and utilise effectively descriptive statistics. Further you will learn how to carry out statistical inference, with the use of probability distributions, sampling and estimation and also how to conduct hypothesis testing. You will learn how to use the SPSS software package and employ it to analyse empirical data.
Learning Outcomes for module:

Upon completion of this module you will be able to

LO1: Gain familiarity with working with Excel and SPSS to analyse data and present output.

LO2: Apply techniques for portraying data through descriptive statistics.

LO3: Apply techniques for statistical inference, hypothesis testing, correlation and regression analysis, and interpret the results.
Full Details of Teaching and Assessment
2025/6, Trimester 1, In Person,
VIEW FULL DETAILS
Occurrence: 001
Primary mode of delivery: In Person
Location of delivery: CRAIGLOCKHAR
Partner:
Member of staff responsible for delivering module: Carles Ibanez
Module Organiser:


Student Activity (Notional Equivalent Study Hours (NESH))
Mode of activityLearning & Teaching ActivityNESH (Study Hours)NESH Description
Face To Face Lecture 22 In the lecture we will cover the data analysis process, from defining a problem to communicating insights, and we will introduce fundamental concepts and relevant software tools.
Face To Face Tutorial 11 In the data analysis tutorial we will provide a structured framework for using data to derive meaningful insights and inform decision-making in various fields. We will deliver a solid understanding of basic statistics, probability, and more advanced statistics.We will use analytical thinking to approach problems.
Face To Face Practical classes and workshops 11 In the data analysis practicals, we will adopt a hands-on approach to summarising and visualising data to identify initial patterns, trends, and anomalies using visual and statistical methods, using spreadsheet tools and statistical siftware.
Online Guided independent study 156 Additional independent learning: we expect you to conduct further additional independent learning to address any additional weaknesses and gaps you identify to achieve the required depth of learning. Use audio, video and online materials: to help you learn at your own pace and explore topics in more depth.
Total Study Hours200
Expected Total Study Hours for Module200


Assessment
Type of Assessment Weighting % LOs covered Week due Length in Hours/Words Description
Class Test 15 2~3 Week 6 HOURS= 50 mins The test consists of a set of multiple choice questions covering the material covered in lectures and tutorials from the first half of the module.
Class Test 15 2~3 Week 9 HOURS= 50 Mins The test consists of a set of multiple choice questions covering the material covered in lectures and tutorials from the second half of the module.
Report 30 2~3 Week 11 , WORDS= 1200 words The report will consist of a series of exercises where you will put in practice the theoretical material covered in lectures and tutorials. The exercises take a global outlook and are resolved using spreadsheet tools and statistical software.
Centrally Time Tabled Examination 40 1~2~3 Exam Period HOURS= 2 Hours The exam will require you to provide accurate computation and interpretation of data analysis outcomes. Full explanations showing a good understanding of the reasons for problem-solving decisions will be expected.
Component 1 subtotal: 60
Component 2 subtotal: 40
Module subtotal: 100
2025/6, Trimester 1, In Person,
VIEW FULL DETAILS
Occurrence: 002
Primary mode of delivery: In Person
Location of delivery: CRAIGLOCKHAR
Partner:
Member of staff responsible for delivering module: Carles Ibanez
Module Organiser:


Student Activity (Notional Equivalent Study Hours (NESH))
Mode of activityLearning & Teaching ActivityNESH (Study Hours)NESH Description
Online Guided independent study 156 Additional independent learning: we expect you to conduct further additional independent learning to address any additional weaknesses and gaps you identify to achieve the required depth of learning. Use audio, video and online materials: to help you learn at your own pace and explore topics in more depth.
Face To Face Lecture 22 In the lecture we will cover the data analysis process, from defining a problem to communicating insights, and we will introduce fundamental concepts and relevant software tools.
Face To Face Tutorial 11 In the data analysis tutorial we will provide a structured framework for using data to derive meaningful insights and inform decision-making in various fields. We will deliver a solid understanding of basic statistics, probability, and more advanced statistics.We will use analytical thinking to approach problems.
Face To Face Practical classes and workshops 11 In the data analysis practicals, we will adopt a hands-on approach to summarising and visualising data to identify initial patterns, trends, and anomalies using visual and statistical methods, using spreadsheet tools and statistical siftware.
Total Study Hours200
Expected Total Study Hours for Module200


Assessment
Type of Assessment Weighting % LOs covered Week due Length in Hours/Words Description
Class Test 15 2~3 Week 6 HOURS= 50 mins The test consists of a set of multiple choice questions covering the material covered in lectures and tutorials from the first half of the module.
Class Test 15 2~3 Week 9 HOURS= 50 Mins The test consists of a set of multiple choice questions covering the material covered in lectures and tutorials from the second half of the module.
Report 30 2~3 Week 11 , WORDS= 1200 words The report will consist of a series of exercises where you will put in practice the theoretical material covered in lectures and tutorials. The exercises take a global outlook and are resolved using spreadsheet tools and statistical software.
Centrally Time Tabled Examination 40 1~2~3 Exam Period HOURS= 2 Hours The exam will require you to provide accurate computation and interpretation of data analysis outcomes. Full explanations showing a good understanding of the reasons for problem-solving decisions will be expected.
Component 1 subtotal: 60
Component 2 subtotal: 40
Module subtotal: 100

Indicative References and Reading List - URL:
Data Analysis
 

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