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2016/17 Undergraduate Module Catalogue

LUBS1535 Excel for Business Analytics

10 creditsClass Size: 120

Module manager: Prof Bill Gerrard
Email: W.J.Gerrard@lubs.leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2016/17

Pre-requisite qualifications

A Level Mathematics or Statistics Grade B

This module is mutually exclusive with

LUBS1260	Mathematics for Economics and Business 1
LUBS1280	Mathematical Economics
LUBS1525	Analytical Methods

This module is approved as a discovery module

Module summary

This module provides an Excel-based introduction to the application of analytical techniques used in business analytics.

Objectives

This modules aims to give students an introduction to the use of Excel in applying the principal analytical techniques used in business analytics.

Learning outcomes
Learning Outcomes - Knowledge/Application
Upon completion of this module students will be able to demonstrate accurate, in-depth and thorough knowledge of analytical techniques and how to apply these techniques to business problems using Excel.

Learning Outcomes - Skills
Upon completion of this module students will be able to:

Subject specific
1. Apply appropriate analytical techniques to analyse business data using Excel to support management decision making

Transferable
1. Analytical skills - mathematical/numerical/statistical
2. Microsoft Excel
3. Communication skills - written
4. Creative problem solving
5. Critical thinking - reviewing evidence; interpreting results
6. Research skills
7. Use of knowledge

Skills outcomes
Upon completion of this module students will be able to apply appropriate analytical techniques using Excel to analyse business data in support of management decision making.

Syllabus

Indicative content:
1. The nature of data analytics
2. The use of Excel as an analytical tool
3. Exploratory data analysis
4. Data visualisation
5. Descriptive data mining: clustering and data reduction
6. Investigating mean differences
7. Modelling continuous outcomes
8. Modelling with categorical data
9. Model diagnostics

Teaching methods

Delivery type	Number	Length hours	Student hours
Lecture	22	1.00	22.00
Tutorial	9	1.00	9.00
Private study hours			69.00
Total Contact hours			31.00
Total hours (100hr per 10 credits)			100.00

Private study

Private Study
2 hours reading per lecture = 44 hours
2 hours preparation per tutorial = 18 hours
Revision = 7 hours
Total private study = 69 hours

Opportunities for Formative Feedback

Student progress will be monitored principally by tutorial performance. All tutorials will require the completion of a practical assignment in advance. Selected assignments will be submitted and marked to provide feedback on student performance (including written communication skills). In addition there will be regular VLE progress tests.

Methods of assessment

Exams

Exam type	Exam duration	% of formal assessment
Unseen exam	1 hr 30 mins	100.00
Total percentage (Assessment Exams)		100.00

Resit will be assessed by the same methodology as the first attempt.

Reading list

There is no reading list for this module

Last updated: 29/04/2016

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