# STAT10060 Statistical Modelling

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.

Show/hide contentOpenClose All

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
Autonomous Student Learning

88

Lectures

24

Tutorial

6

Computer Aided Lab

6

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:
ECON20040 - Statistics for Economists, 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

50

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

50

Carry forward of passed components
No

Resit In Terminal Exam
Autumn Yes - 2 Hour
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
Ms Claire Bergin Tutor
Thiago Da Silva Cardoso Tutor
Kate Finucane Tutor
Mr Brian Hassett Tutor
Hannah Kane Tutor
Mr Chaoyi Lu Tutor
Ms Xu Lu Tutor
Dr Fabian Ofurum Tutor
Niyati Seth Tutor
Mr Ryan Smith Tutor
Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.

Spring

Lecture Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Fri 15:00 - 15:50
Lecture Offering 1 Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 Mon 16:00 - 16:50
Tutorial Offering 1 Week(s) - 22, 24, 26, 30, 32 Mon 11:00 - 11:50
Tutorial Offering 2 Week(s) - 22, 24, 26, 30, 32 Wed 17:00 - 17:50
Tutorial Offering 3 Week(s) - 22, 24, 26, 30, 32 Mon 10:00 - 10:50
Tutorial Offering 4 Week(s) - 22, 24, 26, 30, 32 Wed 09:00 - 09:50
Tutorial Offering 5 Week(s) - 22, 24, 26, 30, 32 Wed 11:00 - 11:50
Tutorial Offering 6 Week(s) - 22, 24, 26, 30, 32 Thurs 11:00 - 11:50
Computer Aided Lab Offering 1 Week(s) - 21, 23, 25, 29, 31, 33 Mon 11:00 - 11:50
Computer Aided Lab Offering 2 Week(s) - 21, 23, 25, 29, 31, 33 Wed 17:00 - 17:50
Computer Aided Lab Offering 3 Week(s) - 21, 23, 25, 29, 31, 33 Mon 10:00 - 10:50
Computer Aided Lab Offering 4 Week(s) - 21, 23, 25, 29, 31, 33 Wed 09:00 - 09:50
Computer Aided Lab Offering 5 Week(s) - 21, 23, 25, 29, 31, 33 Wed 11:00 - 11:50
Computer Aided Lab Offering 6 Week(s) - 21, 23, 25, 29, 31, 33 Thurs 11:00 - 11:50
Spring