BIOL209-19S1 (C) Semester One 2019

Biological Data Analysis

15 points
18 Feb 2019 - 23 Jun 2019


Introductory statistics with specific examples for biologists. This course is required for all students in BIOL.

The overall aim of BIOL209 is to introduce you to presentation of results, statistical analyses and
interpretation of experimental data, as they apply to biological research. The biological focus applies both to the choice of relevant methods and the specific examples discussed. The examples will cover a wide range of biology, from biochemistry to ecology, so that the course is applicable across all biological disciplines. One aim of the course is to prepare students for undergraduate analytical exercises, postgraduate research and jobs in research organisations. BIOL209 progresses from concepts of central tendency probability distributions, then on to hypothesis testing of various types.

Learning Outcomes

As a student in this course, I will develop the ability to:
By the end of this course, you should have achieved the following:
1. A clear understanding of basic statistical principles;
2. Proficiency in the transcription and manipulation of data;
3. A basic understanding of a wide range of parametric and non-parametric statistical tests, including two sample tests, regression, correlation and analysis of variance;
4. Proficiency in the analysis of a wide range of biological data.

Transferable Skills Register
As a student in this course, I will develop the following skills:
 Understand statistical results presented in research papers and technical reports. (The ability to
critically evaluate and interpret statistical information is not only essential in higher-level courses but
is a part of every day life.)
 Ability to apply basic concepts in exploratory data analysis. (This is important for distinguishing
between different types of data, methods of summarising data both graphically and through summary statistics.)
 Knowledge of the basics of collecting data and generating descriptive statistics. (This is essential for all higher-level courses that include laboratory or field based research activities.)
 Ability to apply the appropriate test and draw appropriate conclusions from the test output. (This is important aspect of research and its application.)
 Interpretation and communication skills. (The ability to describe what the results mean in the context of the problem and being able to explain the results to someone else is essential for any professional career.)


STAT101 or 15 points of 100 level MATH

Timetable 2019

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Monday 11:00 - 12:00 A3 Lecture Theatre 18 Feb - 7 Apr
29 Apr - 2 Jun
Lecture B
Activity Day Time Location Weeks
01 Tuesday 08:00 - 09:00 Meremere 108 Lecture Theatre 18 Feb - 7 Apr
29 Apr - 2 Jun
Computer Lab A
Activity Day Time Location Weeks
01 Friday 12:00 - 14:00 Jack Erskine 248 Computer Lab 18 Feb - 7 Apr
29 Apr - 2 Jun
02 Friday 14:00 - 16:00 Ernest Rutherford 212 Computer Lab 18 Feb - 7 Apr
29 Apr - 2 Jun
03 Friday 16:00 - 18:00 Rehua 008 Computer Lab 18 Feb - 7 Apr
29 Apr - 2 Jun
Drop in Class A
Activity Day Time Location Weeks
01 Tuesday 12:00 - 13:00 Putaiao Koiora 275 3 Jun - 9 Jun
Optional A
Activity Day Time Location Weeks
01 Monday 09:00 - 10:00 Jack Erskine 315 18 Mar - 7 Apr
29 Apr - 2 Jun

Timetable Note

Feedback from previous Course Surveys
The course has not had a course survey in the last couple of years (we hope to this year). But feedback during the course helps us to improve the course. If you have any positive or negative comments, feel free to bring them to the lecturer, or Dave Kelly as course coordinator, at any time. If you want to make a complaint anonymously, the lab demonstrators will act on your information in confidence, or approach a staff-student liaison person in the School of Biological Sciences. However, we try to be approachable. Don't hesitate to get in touch if you have any problems about your work, or any personal difficulties. If a problem does arise, it is important to let one of us know as soon as possible so that corrective action can be taken quickly.

Course Coordinator / Lecturer

Dave Kelly


Daniel Stouffer and David Schiel

Guest Lecturer

Dr Richard White (School of Biological Sciences)


Assessment Due Date Percentage 
Final Exam 60%
Lab assessments 40%

Textbooks / Resources

Recommended Reading

Crawley, M.J; Statistics: an introduction using R; 2nd; John Wiley & Sons, 2014 (This is available from the University Bookshop and Amazon. It can also be accessed via the library: Option 1: Connect to electronic resource Option 2: Connect to electronic resource E).

Course links

Course Outline

Indicative Fees

Domestic fee $883.00

International fee $4,000.00

* Fees include New Zealand GST and do not include any programme level discount or additional course related expenses.

For further information see School of Biological Sciences.

All BIOL209 Occurrences

  • BIOL209-19S1 (C) Semester One 2019