STATS 310 : Introduction to Statistical Inference

Science

2021 Semester One (1213) (15 POINTS)

Course Prescription

Estimation, likelihood methods, hypothesis testing, multivariate distributions, linear models.

Course Overview

This course gives an introduction to the fundamental theory in statistical inference. The knowledge taught in this course is fundamental in statistical inference and necessary to carry out decent statistical research. The prerequisites are a basic knowledge of probability, statistics and mathematics (Stage 2, basically). It comprises the topics in discrete and continuous random variables, multivariate distributions, sampling theory for the normal distribution, parametric estimation, hypothesis testing, and linear regression models. It is a statistical theory paper. It is important that a student is able to use both calculus and linear algebra confidently in order to cope with this paper.

Course Requirements

Prerequisite: STATS 210 or 225, and 15 points from MATHS 208, 250 or equivalent Restriction: STATS 732

Capabilities Developed in this Course

Capability 1: Disciplinary Knowledge and Practice
Capability 2: Critical Thinking
Capability 3: Solution Seeking
Capability 4: Communication and Engagement
Capability 5: Independence and Integrity
Graduate Profile: Bachelor of Science

Learning Outcomes

By the end of this course, students will be able to:
  1. Demonstrate an understanding of discrete and continuous random variables. (Capability 1 and 3)
  2. Develop and demonstrate the knowledge of using calculus to derive formulae for distributions. (Capability 1, 2 and 3)
  3. Understand and analyse multivariate distributions (Capability 1, 2, 3, 4 and 5)
  4. Understand and analyse the sampling theory for the normal distribution. (Capability 1, 2, 3 and 4)
  5. Learn and use the theory for parameter estimation and find and carry out a likelihood analysis. (Capability 1, 2, 3, 4 and 5)
  6. Learn and use the formula for hypothesis testing. (Capability 1, 2, 3, 4 and 5)
  7. Learn and use the theory for linear regression and the associated geometry. (Capability 1, 2, 3, 4 and 5)

Assessments

Assessment Type Percentage Classification
Assignments 30% Individual Coursework
Test 20% Individual Test
Final Exam 50% Individual Examination
Assessment Type Learning Outcome Addressed
1 2 3 4 5 6 7
Assignments
Test
Final Exam
Must pass the exam (50/100 marks)

Special Requirements

No special requirements

Workload Expectations

This course is a standard 15 point course and students are expected to spend 150 hours per semester involved in each 15 point course that they are enrolled in.

For this course, you can expect 3 hours of lectures, a 2 hour tutorial, 2.5 hours of reading and thinking about the content and 2.5 hours of work on assignments and/or test preparation.

Delivery Mode

Campus Experience

Attendance is expected at scheduled activities including tutorials to complete credit for components of the course.
Lectures will be available as recordings. Other learning activities including tutorials will not be available as recordings.
The course will not include live online events including tutorials.
Attendance on campus is required for the test/exam.
The activities for the course are scheduled as a standard weekly timetable.

The course is available online to students studying remote due to COVID-19 only.

Learning Resources

There is a comprehensive coursebook.
Tutorial materials will be available on Canvas.

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.

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.

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.

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.

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 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.

Learning Continuity

In the event of an unexpected disruption we undertake to maintain the continuity and standard of teaching and learning in all your courses throughout the year. If there are unexpected disruptions the University has contingency plans to ensure that access to your course continues and your assessment is fair, and not compromised. Some adjustments may need to be made in emergencies. You will be kept fully informed by your course co-ordinator, and if disruption occurs you should refer to the University Website for information about how to proceed.

Level 1:  Delivered normally as specified in delivery mode
Level 2: You will not be required to attend in person.  All teaching and assessment will have a remote option.  The following activities will also have an on campus / in person option: Lectures, labs, tutorials, office hours.
Level 3 / 4: All teaching activities and assessments are delivered remotely

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.

Published on 17/04/2021 08:17 p.m.