CE2STA: Statistical Analysis

Module code: CE2STA

Module provider: School of Construction Management and Engineering, School of Built Environment

Credits: 20

Level: Level 2 (Intermediate)

When you'll be taught: Semester 2

Module convenor: Dr Christos Halios, email: c.halios@reading.ac.uk

Module co-convenor: Dr Eugene Mohareb, email: e.mohareb@reading.ac.uk

Pre-requisite module(s):

Co-requisite module(s):

Pre-requisite or Co-requisite module(s):

Module(s) excluded:

Placement information: NA

Academic year: 2024/5

Available to visiting students: Yes

Talis reading list: No

Last updated: 21 May 2024

Overview

Module aims and purpose

The aim of this module is to provide students with principles of statistical data analysis and a number of key statistical data analysis techniques required for the evaluation of a dataset and drawing an informed and unbiased conclusion. 

This module introduces key statistical methods to assess real-world engineering problems. It explains how to use both basic and more advanced statistical techniques and introduces quantitative data analysis methods that are useful in engineering subjects including Architectural Engineering. Using a number of datasets from a range of science and engineering applications, students will learn practical statistical techniques and fundamental principles, as well as using software to analyse data. In addition, student will learn the main differences between parametric and nonparametric analysis. 

Module learning outcomes

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

1. Present and interpret statistical results scientifically and explain assumptions underlying statistical techniques; 
2. Select and apply appropriate statistical methods (including the use statistical software) for exploring sets of data of engineering applications; 
3. Select appropriate techniques to find any associations between variables in a dataset and perform data fitting and to evaluate the fit results, including errors and goodness-of-fit. 

Module content

• The basic concept of measurement 
• Samples and populations 
• Inferential vs descriptive statistics 
• Gaussian and Binomial distributions 
• Analysis of variance  
• Linear regression analysis 
• Confidence intervals 
• Random vs systemic error 
• Presenting and summarising data 
• Assumptions for parametric tests: Parametric vs nonparametric statistics 
• Non-parametric hypothesis tests based on ranks 
• Nominal data: Chi-squared goodness of fit tests  
• Normality testing 
• Rank correlations 

Structure

Teaching and learning methods

Teaching in this module will be by means of lectures, tutorials and practical classes using facilities available in the computer laboratory. These sessions will be complemented by project activities and guided independent study. 

Study hours

At least 30 hours of scheduled teaching and learning activities will be delivered in person, with the remaining hours for scheduled and self-scheduled teaching and learning activities delivered either in person or online. You will receive further details about how these hours will be delivered before the start of the module.

Please note the independent study hours above are notional numbers of hours; each student will approach studying in different ways. We would advise you to reflect on your learning and the number of hours you are allocating to these tasks.

Semester 1 The hours in this column may include hours during the Christmas holiday period.

Semester 2 The hours in this column may include hours during the Easter holiday period.

Summer The hours in this column will take place during the summer holidays and may be at the start and/or end of the module.

Assessment

Requirements for a pass

Students need to achieve an overall module mark of 40% to pass this module.

Summative assessment

Penalties for late submission of summative assessment

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

Assessments with numerical marks

• 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 three working days;
• the mark awarded due to the imposition of the penalty shall not fall below the threshold pass mark, namely 40% in the case of modules at Levels 4-6 (i.e. undergraduate modules for Parts 1-3) and 50% in the case of Level 7 modules offered as part of an Integrated Masters or taught postgraduate degree programme;
• where the piece of work is awarded a mark below the threshold pass mark prior to any penalty being imposed, and is submitted up to three working days after the original deadline (or any formally agreed extension to the deadline), no penalty shall be imposed;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

Assessments marked Pass/Fail

• where the piece of work is submitted within three working days of the deadline (or any formally agreed extension of the deadline): no penalty will be applied;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension of the deadline): a grade of Fail will be awarded.

The University policy statement on penalties for late submission can be found at: /cqsd/-/media/project/functions/cqsd/documents/qap/penaltiesforlatesubmission.pdf

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.

Formative assessment

Formative assessment is any task or activity which creates feedback (or feedforward) for you about your learning, but which does not contribute towards your overall module mark.

Formative assessment will be provided in practical classes.  

Reassessment

Additional costs