|Module Name||Introduction to Statistics I (Probability)|
|ECTS Weighting||5 ECTS|
|Semester taught||Semester 1|
|Module Coordinator/s||Fergal Shevlin|
Module Learning Outcomes
- Understand the elementary concepts of probability models.
- Apply various probability models to practical problems in a range of disciplines.
- Distinguish between discrete and continuous random variables.
- Appreciate the elementary properties of random variables.
- Sample Space and Probability: Sets; Probabilistic Models; Conditional Probability; Total Probability.
- Theorem and Bayes’ Rule; Independence; Counting.
- Discrete Random Variables: Probability Mass Functions; Functions of Random Variables.
- Expectation, Mean, and Variance; Joint PMFs of Multiple Random Variables; Conditioning.
- General Random Variables: Continuous Random Variables and PDFs; Cumulative Distribution.
- Functions; Normal Random Variables; Joint PDFs of Multiple Random Variables; Conditioning.
- Continuous Bayes’ Rule.
Teaching and learning Methods
Lectures, homework, tutorials.
|Assessment Component||Brief Description||Learning Outcomes Addressed||% of total||Week set||Week Due|
|Examination||Take-at-home examination, time-limited.||LO1,2,3,4.||100|||||
Take-at-home examination, time-limited, 100%.
Contact Hours and Indicative Student Workload
|Contact Hours (scheduled hours per student over full module), broken down by:||33 hours|
|Lectures (11 weeks x 2 hours.)||22 hours|
|Tutorials (11 weeks x 1 hour.)||11 hours|
|Independent study (outside scheduled contact hours), broken down by:||92 hours|
|Suggested lecture preparation (11 weeks x 3 hours.)||33 hours|
|Suggested homework problem-solving (11 weeks x 3 hours.)||33 hours|
|Exam preparation (2 weeks x 13 hours.)||26 hours|
|Total Hours||125 hours|
Recommended Reading List
Extensive on-line course material associated with “Introduction to Probability”, 2nd Edition, Bertsekas and Tsitsiklis, Athena Scientific.
See TCD Blackboard.