Analytics for Marketing

by University of Southampton Claim Listing

This module introduces some key concepts about the use of some basic statistical and analytical techniques within the marketing context. Students will learn through a combination of lectures, group work, practical (computer-lab) sessions (where needed), and self-study. After studying this module, st

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img Duration

150 Hours

Course Details

Module overview

This module introduces some key concepts about the use of some basic statistical and analytical techniques within the marketing context. Students will learn through a combination of lectures, group work, practical (computer-lab) sessions (where needed), and self-study. After studying this module, students will be able to apply these techniques to analyse data in practice.

Learning Outcomes

Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

  • implement analytic models to support marketing decision making.

  • differentiate suitable approaches for a range of analytics tasks;

Subject Specific Practical Skills

Having successfully completed this module you will be able to:

  • apply and critically evaluate marketing intelligence techniques and use them to draw practical recommendations;

  • apply marketing concepts and evaluate them by using marketing intelligence techniques.

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

  • how to use analytic techniques to evaluate the quality of data for supporting marketing decisions;

  • how to apply standard analytical tools to support marketing decisions.

Transferable and Generic Skills

Having successfully completed this module you will be able to:

  • explain concepts clearly and critically apply findings.

Syllabus

  • Data types and their sources

  • Univariate/Descriptive statistics

  • Probability, cross tabulation and chi square

  • Discrete, Continuous and Sampling distributions

  • Interval estimation

  • Hypothesis testing

  • Comparisons of means

  • Correlation and linear regression

Teaching and learning methods

The basic principal of the teaching and learning strategy for this unit is to encourage you to actively engage in the subject matter through guided self-discovery of the material which will include: Reading; lecture slides; case studies; discussion and debate.

Formative

This is how we’ll give you feedback as you are learning. It is not a formal test or exam.

Class Exercise

  • Assessment Type: Formative

  • Feedback: Formative feedback will be provided to students during lectures, class exercises, computer laboratories, office hours, and via email when questions are asked of the module leader.

  • Final Assessment: No

  • Group Work: No

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    University Road, Southampton

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