STAT41060 Probability and Statistics

Academic Year 2022/2023

Axioms of probability. Discrete and continuous manual and classical distributions. Expectations and variances. Maximum likelihood and method of moments. Sampling theory. Confidence intervals and hypothesis testing. Power. Use of R for modelling. Regression. Two-sample tests and confidence intervals. Tests for independence. Tests for variance.

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Curricular information is subject to change

Learning Outcomes:

Active task based learning in tutorials. Material covered in lectures in traditional slides and with code demos. Coding also done live in tutorials. Some blended support via lecture and tutorial material on video. Assignments with marked feedback as individual student exercises.

Indicative Module Content:

Active task based learning in tutorials. Material covered in lectures in traditional slides and with code demos. Coding also done live in tutorials. Some blended support via lecture and tutorial material on video. Assignments with marked feedback as individual student exercises.

Student Effort Hours: 
Student Effort Type Hours
Lectures

48

Total

48

Approaches to Teaching and Learning:
Live lectures and tutorials. Code demos. Some blended learning support with lecture and tutorial videos. 
Requirements, Exclusions and Recommendations

Not applicable to this module.


Module Requisites and Incompatibles
Incompatibles:
STAT20060 - Statistics and Probability


 
Assessment Strategy  
Description Timing Open Book Exam Component Scale Must Pass Component % of Final Grade
Examination: Two hour end of semester exam 2 hour End of Trimester Exam No Other No

80

Assignment: 3 equally weighted assignments, code and by hand material. Throughout the Trimester n/a Other No

20


Carry forward of passed components
Yes
 
Resit In Terminal Exam
Spring Yes - 2 Hour
Please see Student Jargon Buster for more information about remediation types and timing. 
Feedback Strategy/Strategies

• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment

How will my Feedback be Delivered?

Individually marked assignments returned. Group feedback in tutorials.

Name Role
Thais Pacheco Menezes Tutor