STAT10060 Statistical Modelling

Academic Year 2021/2022

This course is an introduction to some of the basic statistical methods and tools used for analyzing data and make decisions. Core concepts will be presented using practical data examples, focusing on applications and critical evaluation. The module will introduce these methods also using the statistical software R.
Main topics covered:
- Introduction and basics of inference.
- Comparing two populations: Confidence intervals and hypothesis testing for the difference between population means and population proportions - Independent and paired samples - Sample size calculations.
- Analysis of categorical data: One and two-way frequency tables - Hypothesis testing - Test for association.
- Simple linear regression: Correlation - Regression line - Checking model adequacy - Using the model for inference and prediction.
- Analysis of variance: One-way ANOVA - Multiple comparisons - Randomized block experiments - Two-way ANOVA.

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Curricular information is subject to change

Learning Outcomes:

On completion of this module, students should have acquired the following skills:
- Perform basic inference for comparing two populations
- Being able to analyze and perform inference on categorical data in the form of frequency tables
- Fit, assess and use the simple linear regression model
- Conduct analysis of variance for comparing multiple populations and investigate effect of factors
- Use the statistical software R to implement the methods and being able to interpret the relevant output
- Have a general understanding of all the statistical methods introduced and being able to use them according to the context and purpose of analysis

Student Effort Hours: 
Student Effort Type Hours
Lectures

24
Tutorial

6
Computer Aided Lab

6
Autonomous Student Learning

88
Total

124
Approaches to Teaching and Learning:
Lectures, tutorials, computer labs, enquiry and problem-based learning. 
Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Incompatibles:
MATH10250 - Intro Calculus for Engineers , STAT20080 - Regression & ANOVA, STAT20090 - Stat Infer & Good of Fit


 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Continuous Assessment: Assignments, MCQ, Computer Lab Exam Varies over the Trimester n/a Standard conversion grade scale 40% No

40
Examination: End of Trimester Exam 2 hour End of Trimester Exam No Standard conversion grade scale 40% No

60

Carry forward of passed components
No
 
Resit In Terminal Exam
Autumn Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Not yet recorded.

Name Role
Dr Codrin Andrei Lecturer / Co-Lecturer
Dr Fabian Ofurum Tutor