STATS 125 : Probability and its Applications
Science
2020 Semester Two (1205) (15 POINTS)
Course Prescription
Course Overview
The course concentrates on probability models and their applications in a variety of fields. Probability underpins both statistics and (stochastic) operations research. As such this is a core course for students in the Statistics and Probability pathway or a Data Science Specialisation and optional for those pursuing the Applied Statistics pathway or a Statistics major. Probability models are also used in disciplines as varied as commerce and biology (e.g. calculating the probability that a share price will exceed a certain level or the probability that a population will become extinct). This means the course is useful for students with varied interests, as well as those who have Maths or Statistics as their main interest. STATS 125 is a prerequisite for STATS 210. Students with a weak mathematics background will need to take (and pass) MATHS 102 before taking STATS 125 and MATHS 108.
Topics covered are probability, conditional probability, Bayes' theorem, discrete distributions, expectation and variance, joint and conditional discrete distributions, definition and examples of Markov chains, random walks, hitting probabilities and times, equilibrium distributions. Illustrations will be drawn from a wide variety of applications including finance and economics, genetics, bioinformatics and other areas of biology, telecommunication networks, games, gambling and risk, and forensic science.
Capabilities Developed in this Course
| Capability 1: | Disciplinary Knowledge and Practice |
| Capability 2: | Critical Thinking |
| Capability 3: | Solution Seeking |
| Capability 4: | Communication and Engagement |
Learning Outcomes
- Demonstrate the use of probability rules, discrete distributions, joint distributions and Markov chains to solve problems (Capability 1 and 3)
- Translate information given in words into correct probability statements (Capability 1 and 3)
- Select an appropriate discrete probability model to solve a problem (Capability 1 and 3)
- Produce and clearly explain mathematical calculations and reasoning (Capability 1, 3 and 4)
- Interpret their solution to a probability problem with reference to the context of the problem (Capability 1 and 4)
- Recognise and specify the limitations of a simple probability model in a given context (Capability 1 and 2)
- Differentiate between reasonable and unreasonable solutions to probability problems (Capability 1, 2 and 3)
Assessments
| Assessment Type | Percentage | Classification |
|---|---|---|
| Assignments | 18% | Individual Coursework |
| Quizzes | 12% | Individual Coursework |
| Test | 20% | Individual Test |
| Final Exam | 50% | Individual Examination |
| 4 types | 100% |
| Assessment Type | Learning Outcome Addressed | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | ||||
| Assignments | ||||||||||
| Quizzes | ||||||||||
| Test | ||||||||||
| Final Exam | ||||||||||
The plussage is applied and the final mark is calculated based on 20% test and 50% final exam or 10% test and 60% final exam.
A minimum of 45% in the final exam is necessary to pass the course (in addition to a minimum overall mark of 50%).
Tuākana
The Department of Statistics has a team of eight Tuākana tutors covering our Stage 1 and Stage 2 courses, including STATS 125. For details and online session times, visit https://www.auckland.ac.nz/en/science/study-with-us/maori-and-pacific-at-the-faculty/tuakana-programme.html.
Key Topics
Learning Resources
Workload Expectations
This course is a standard 15 point course and students are expected to spend 10 hours per week involved in each 15 point course that they are enrolled in.
For this course, you can expect 3 hours of lectures, a 1-hour tutorial, 3 hours of reading and thinking about the content and 3 hours of work on assignments, quizzes and/or test preparation.
Digital Resources
Course materials are made available in a learning and collaboration tool called Canvas which also includes reading lists and lecture recordings (where available).
Please remember that the recording of any class on a personal device requires the permission of the instructor.
Copyright
The content and delivery of content in this course are protected by copyright. Material belonging to others may have been used in this course and copied by and solely for the educational purposes of the University under license.
You may copy the course content for the purposes of private study or research, but you may not upload onto any third party site, make a further copy or sell, alter or further reproduce or distribute any part of the course content to another person.
Academic Integrity
The University of Auckland will not tolerate cheating, or assisting others to cheat, and views cheating in coursework as a serious academic offence. The work that a student submits for grading must be the student's own work, reflecting their learning. Where work from other sources is used, it must be properly acknowledged and referenced. This requirement also applies to sources on the internet. A student's assessed work may be reviewed against online source material using computerised detection mechanisms.
Inclusive Learning
All students are asked to discuss any impairment related requirements privately, face to face and/or in written form with the course coordinator, lecturer or tutor.
Student Disability Services also provides support for students with a wide range of impairments, both visible and invisible, to succeed and excel at the University. For more information and contact details, please visit the Student Disability Services’ website at http://disability.auckland.ac.nz
Special Circumstances
If your ability to complete assessed coursework is affected by illness or other personal circumstances outside of your control, contact a member of teaching staff as soon as possible before the assessment is due.
If your personal circumstances significantly affect your performance, or preparation, for an exam or eligible written test, refer to the University’s aegrotat or compassionate consideration page: https://www.auckland.ac.nz/en/students/academic-information/exams-and-final-results/during-exams/aegrotat-and-compassionate-consideration.html.
This should be done as soon as possible and no later than seven days after the affected test or exam date.
Student Feedback
During the course Class Representatives in each class can take feedback to the staff responsible for the course and staff-student consultative committees.
At the end of the course students will be invited to give feedback on the course and teaching through a tool called SET or Qualtrics. The lecturers and course co-ordinators will consider all feedback.
Your feedback helps to improve the course and its delivery for all students.
Student Charter and Responsibilities
The Student Charter assumes and acknowledges that students are active participants in the learning process and that they have responsibilities to the institution and the international community of scholars. The University expects that students will act at all times in a way that demonstrates respect for the rights of other students and staff so that the learning environment is both safe and productive. For further information visit Student Charter (https://www.auckland.ac.nz/en/students/forms-policies-and-guidelines/student-policies-and-guidelines/student-charter.html).
Disclaimer
Elements of this outline may be subject to change. The latest information about the course will be available for enrolled students in Canvas.
In this course you may be asked to submit your coursework assessments digitally. The University reserves the right to conduct scheduled tests and examinations for this course online or through the use of computers or other electronic devices. Where tests or examinations are conducted online remote invigilation arrangements may be used. The final decision on the completion mode for a test or examination, and remote invigilation arrangements where applicable, will be advised to students at least 10 days prior to the scheduled date of the assessment, or in the case of an examination when the examination timetable is published.