STAT202-24S2 (C) Semester Two 2024

Regression Modelling

15 points

Details:
Start Date: Monday, 15 July 2024
End Date: Sunday, 10 November 2024
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 28 July 2024
  • Without academic penalty (including no fee refund): Sunday, 29 September 2024

Description

Regression models are the most widely used statistical tools for examining the relationships among variables. This course will provide a practical introduction to the fundamentals of regression modelling.

This course is of interest to anyone majoring in statistics and forestry, as well as students from other disciplines (e.g. biology, commerce, etc.) who want to increase the breadth of their statistical knowledge base.

Regression models are the most widely used statistical tools for examining the relationships among variables. We cover the core concepts in regression modelling, with an emphasis on problem solving as applied to real data. We use R, one of the mostly widely used statistical packages, but no prior knowledge of R is assumed.

Learning Outcomes

  • On completing this course you will
  • be able to analyze data using simple and multiple regression models as well as logistic regression
  • understand the relationship between regression and ANOVA
  • understand diagnostics for testing modelling assumptions
  • understand methods for model selection
  • be able to interpret computer output, and be able to write reports that analyse data and interpret computer output

Prerequisites

STAT101 or DATA101 or 15 points from 100-level MATH or EMTH (excluding MATH110)

Restrictions

FORE210, STAT220, FORE224, STAT224

Timetable 2024

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Thursday 13:00 - 14:00 E5 Lecture Theatre
15 Jul - 25 Aug
9 Sep - 20 Oct
Lecture B
Activity Day Time Location Weeks
01 Friday 11:00 - 12:00 A3 Lecture Theatre
15 Jul - 25 Aug
9 Sep - 20 Oct
Lecture C
Activity Day Time Location Weeks
01 Monday 10:00 - 11:00 E5 Lecture Theatre
15 Jul - 25 Aug
9 Sep - 20 Oct
Computer Lab A
Activity Day Time Location Weeks
01 Wednesday 14:00 - 15:00 Rehua 008 Computer Lab
15 Jul - 25 Aug
9 Sep - 13 Oct
02 Wednesday 13:00 - 14:00 Ernest Rutherford 464 Computer Lab
15 Jul - 25 Aug
9 Sep - 20 Oct
03 Wednesday 15:00 - 16:00 Jack Erskine 001 Computer Lab
15 Jul - 25 Aug
9 Sep - 20 Oct

Timetable Note

This course is co-coded with FORE224. Students must register for tutorial sessions which commence on the second week of the course. There is a direct link from your personal Learn page for the course to the student entry point for My Timetable that enables you to self-allocate into one of three lab streams.

Course Coordinator / Lecturer

Luis Apiolaza

Lecturer

Jenny Harlow

Assessment

Assessment Due Date Percentage  Description
Lab Assignments 50% 10 Labs of 5% each
Final Exam 50% A minimum pass of 40% is required to pass the course.

Indicative Fees

Domestic fee $847.00

International fee $4,988.00

* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.

For further information see Mathematics and Statistics .

All STAT202 Occurrences

  • STAT202-24S2 (C) Semester Two 2024
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