ULMS Electronic Module Catalogue

The information contained in this module specification was correct at the time of publication but may be subject to change, either during the session because of unforeseen circumstances, or following review of the module at the end of the session. Queries about the module should be directed to the member of staff with responsibility for the module.
Title Data Analysis for Accountants
Code ACFI120
Coordinator Mr MJ Swift
Finance and Accounting
Mark.Swift@liverpool.ac.uk
Year CATS Level Semester CATS Value
Session 2021-22 Level 4 FHEQ Second Semester 15

Pre-requisites before taking this module (other modules and/or general educational/academic requirements):

 

Modules for which this module is a pre-requisite:

 

Programme(s) (including Year of Study) to which this module is available on a required basis:

 

Programme(s) (including Year of Study) to which this module is available on an optional basis:

 

Teaching Schedule

  Lectures Seminars Tutorials Lab Practicals Fieldwork Placement Other TOTAL
Study Hours   8

      24

6

12

50
Timetable (if known)   60 mins X 1 totaling 8
 
      120 mins X 1 totaling 24
60 mins X 1 totaling 6
 
 
Private Study 100
TOTAL HOURS 150

Assessment

EXAM Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
             
CONTINUOUS Duration Timing
(Semester)
% of
final
mark
Resit/resubmission
opportunity
Penalty for late
submission
Notes
Assessment 3: Group Presentation Assessment Type: Practical Assessment Size: 5 minutes Weighting: 10% Reassessment Opportunity: Yes Penalty for Late Submission: Standard UoL Penalty Applies Anon  5 minutes    10       
Assessment 1 - Company Performance Analysis Report Assessment Type: Coursework Size: 1250 words Weighting: 30% Reassessment Opportunity: Yes Penalty for Late Submission: Standard UoL Penalty Appl  -1250 words    30       
Assessment 2: Group Company Decision Making Report Assessment Type: Coursework Size: 3000 words Weighting: 60% Reassessment Opportunity: Yes Penalty for Late Submission: Standard UoL Penalty Ap  -3000 words    60       

Aims

This module also aims to develop an understanding of financial statement analysis using financial accounting and ratio analysis skills developed in this and earlier modules. Using the research tools available, students will examine company financial statements and evaluate their position and performance.


Learning Outcomes

(LO1) Students will be able to analyse and interpret financial statements and other financial information and draw appropriate conclusions..

(LO2) Students will be able to calculate and discuss key ratios relevant to company financial statements.

(LO3) Students will be able to examine how the finance function uses data and data analysis to fulfil its roles.

(LO4) Students will be able to use data (financial and non-financial) and the appropriate concepts and techniques to facilitate performance measure and management – supporting the achievement of organisational objectives of value creation and preservation.

(LO5) In the analysis, presentation and interpretation of data, demonstrate consideration of the needs and abilities of the ultimate user of the data.

(S1) Flexible and Adaptable

(S2) A Problem Solver

(S3) Numerate

(S4) Commercially Aware

(S5) An Excellent Verbal and Written Communicator

(S6) Internationally Aware


Teaching and Learning Strategies

Teaching Method: Online Asynchronous Learning Materials
Unscheduled Directed Student Hours: 12
Attendance Recorded: No

Teaching Method : Large Group Teaching
Description: Students will be introduced to core material and discuss how these concepts are applied in business. Students will also be introduced to coursework requirements.
Scheduled Directed Student Hours: 24
Attendance Recorded: No

Teaching Method: Seminar
Description: Smaller group classes working through data sets and how to use them for business decision making and performance analysis
Scheduled Directed Student Hours: 8
Attendance Recorded: No

Teaching Method: Group Study
Description: Bi-weekly 1 hour session to foster student community and engagement by working with others on their ‘active learning’ activities
Scheduled Directed Student Hours: 6
Attendance Recorded: No

Self-Directed Learning Hours: 100
Description: Students will comp lete the required reading and review their notes from lectures. Students will practise data analysis skills using data sets and company financial statements. Students will prepare for their coursework.

Skills Mapping

Skill 1: Flexible and Adaptable
How is this developed: Students will have to complete work as part of a group and this will require being flexible and adaptable so that all group members are able to make good contributions to the assignment.
Mode of assessment: Assessment 2

Skill 2: A Problem Solver
How is this developed: Students will be required to use the tools, techniques and knowledge they gain throughout the module to solve problems that businesses might face.
Mode of assessment: Assessment 1 and Assessment 2

Skill 3: Numerate
How is this developed: Students are required to use financial data to analyse problems and to interpret financial statements.
Mode of assessment: Assessment 1 and Assessment 2

Skill 4: Comm ercially Aware
How is this developed: Students are required to apply their skills to real business data.
Mode of assessment: Assessment 1 and Assessment 2

Skill 5: An Excellent Verbal and Written Communicator
How is this developed: Students will be required to prepare reports and also to deliver a presentation on their work.
Mode of assessment: Assessment 1, Assessment 2, and Assessment 3

Skill 6: Internationally Aware
How is this developed: The companies and cases students will be studying will be international companies.
Mode of assessment: Assessment 1 and Assessment 2


Syllabus

 

- Introduction to data analysis and its importance in analysing business performance and in business decision making.
- Financial statement analysis including reliability of data and limitations of analysis
- Data sources and data visualisation
- Using data for business decision making


Recommended Texts

Reading lists are managed at readinglists.liverpool.ac.uk. Click here to access the reading lists for this module.