# Probability

AUT University

## Course Description

Probability

• ### Host University

AUT University

• ### Location

Auckland, New Zealand

Statistics

• ### Language Level

Taught In English

• ### Prerequisites

715186: Differential and Integral Calculus

715189: Algebra and Discrete Mathematics

• ### Course Level Recommendations

Upper

ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.

### Hours & Credits

• Credit Points

15
• Recommended U.S. Semester Credits
3 - 4
• Recommended U.S. Quarter Units
4 - 6
• ### Overview

Provides the student with conceptual knowledge and techniques for modelling and analysing random experiments and random functions.

STUDENT LEARNING HOURS:
The learning hours are a guide to the total time needed for a student to complete the paper:
Class contact 24
Self directed 102
Total learning hours 150

PRESCRIPTOR:
Provides the student with conceptual knowledge and techniques for modelling and analysing
random experiments and random functions.

LEARNING OUTCOMES:
On successful completion of this paper students will be able to:
1. Solve problems involving the concepts of conditional probability and independence
including Bayes formula.
2. Solve problems involving discrete random variables along with their characteristics
and distributions.
3. Solve problems involving continuous random variables along with their
characteristics and distributions.
4. Solve problems involving bivariate distributions.
5. Apply the Central Limit Theorem.
6. Solve problems involving Markov chains.
7. Use probability to analyse real-life situations such as queues and system reliability.
8. Simulate probability distributions.

CONTENT:
•  Probability space
• Probability concepts
• Conditional probability and independence of events
• Properties of discrete random variables, including expectation, variance and moments
• Common discrete distributions such as Bernoulli, binomial, Poisson, geometric and
• negative binomial
• Properties of continuous distributions including expectation, variance and moments
• Common continuous distributions such as uniform, normal, exponential, gamma and
• beta

### Course Disclaimer

Courses and course hours of instruction are subject to change.

Eligibility for courses may be subject to a placement exam and/or pre-requisites.

Some courses may require additional fees.

Credits earned vary according to the policies of the students' home institutions. According to ISA policy and possible visa requirements, students must maintain full-time enrollment status, as determined by their home institutions, for the duration of the program.

Please reference fall and spring course lists as not all courses are taught during both semesters.

Availability of courses is based on enrollment numbers. All students should seek pre-approval for alternate courses in the event of last minute class cancellations

Please note that some courses with locals have recommended prerequisite courses. It is the student's responsibility to consult any recommended prerequisites prior to enrolling in their course.