RE1INDA-Introduction to Data Analysis

Module Provider: Real Estate and Planning
Number of credits: 10 [5 ECTS credits]
Terms in which taught: Spring term module
Non-modular pre-requisites:
Co-requisites: IC103 Introductory Economics for Business and Finance LW1A05 General Introduction to Law LW101F Introduction to Property Law RE1IAP Investment Appraisal RE1IPB Introductions to Planning and Building RE1PROJ Projects in Real Estate and Planning
Modules excluded:
Current from: 2021/2

Module Convenor: Dr Mike Langen

Type of module:

Summary module description:

The module introduces basic introduces basic statistical concepts and data analysis, focusing on the real estate environment. It introduces statistical terminology and basic concepts, allowing students to systematically analyse and describe quantitative data. Using basic econometric tools, students will learn how a research hypothesis is developed and tested. The module focus is on applications in a real estate context using Microsoft Excel. Therefore, the module further focuses on the use of Excel and on ways to visualise data. 

This module is delivered at the University of Reading and University of Reading Malaysia. 


The module will lay the foundation of analytical methods for real estate. It will enable students to interpret, display and explore data, understand the concept of probabilities and conduct simple hypothesis testing. It will also apply these concepts to real estate analysis.

Assessable learning outcomes:

By the end of the module it is expected that students will be able to:

  • Describe data using both tables and a graphic representation

  • Analyse data and display and explore trends and key summary statistics

  • Understand the concept of probability

  • Identify different types of probability distributions

  • Discuss sampling methods and confidence levels

  • Understand and apply simple hypothesis tes ting

  • Have a basic understanding of econometric modelling

Additional outcomes:

The module aims to encourage the development of analytical and quantitative skills in relation to the application of basic statistics to real estate and business decisions. Students will also improve their ability to translate theoretical concepts to approach practical problems. The relevance of this module will also be understood in its application within future modules related to valuation and the understanding of market dynamics.

Outline content:

  • Introduction to different types of data

  • Data description (central tendency, dispersion, correlation etc.)

  • Probability distribution

  • Data visualisations

  • Hypothesis development

  • Hypothesis testing

  • Econometric modelling and testing (regressions)

Brief description of teaching and learning methods:

The module will be taught in a combination of lectures and practical workshops

Contact hours:
  Autumn Spring Summer
Lectures 10
Practicals classes and workshops 10
Guided independent study:      
    Wider reading (independent) 20 10
    Exam revision/preparation 30
    Preparation for tutorials 20
Total hours by term 0 60 40
Total hours for module 100

Summative Assessment Methods:
Method Percentage
Written exam 100

Summative assessment- Examinations:

The module will be assessed through a two-hour exam.

Summative assessment- Coursework and in-class tests:

Formative assessment methods:

Students will receive feedback on the work they produce on a weekly basis. This will be done through practical sessions (workshops) where they can compare their work with a proposed solution and ask questions to develop their knowledge further. In some workshops they may also be asked to present their work to facilitate the discussion.

Penalties for late submission:

The Support Centres will apply the following penalties for work submitted late:

  • where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of five working days;
  • where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.
The University policy statement on penalties for late submission can be found at:
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Assessment requirements for a pass:

The pass-mark for this module is 40%.

Reassessment arrangements:

Reassessment will be by the same method as for the module's original assessment requirements, subject to variation by the Examination Board where appropriate.

Additional Costs (specified where applicable):

Last updated: 15 April 2021


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