BIOL209-21S1 (C) Semester One 2021

Biological Data Analysis

15 points

Details:
Start Date: Monday, 22 February 2021
End Date: Sunday, 27 June 2021
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 7 March 2021
  • Without academic penalty (including no fee refund): Friday, 14 May 2021

Description

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:

    1. A clear understanding of basic statistical principles (assessment: lab quizzes, midterm test, final exam)
    Related Graduate Attributes and Kaupapa: Critically competent in the core academic discipline, Employable, innovative and enterprising.

    2. Proficiency in the transcription and manipulation of data (assessment: lab quizzes, midterm test, final exam)
    Related Graduate Attributes and Kaupapa: Critically competent in the core academic discipline, Employable, innovative and enterprising

    3. A basic understanding of a wide range of parametric and non-parametric statistical tests (assessment: lab quizzes, final exam)
    Related Graduate Attributes and Kaupapa: Critically competent in the core academic discipline, Biculturally Competent and Confident (kaupapa 1), Employable, innovative and enterprising

    4. Proficiency in the analysis of a wide range of biological data, including the ability to place the data in an appropriate context (assessment: lab quizzes, midterm test, final exam)
    Related Graduate Attributes and Kaupapa: Critically competent in the core academic discipline, Employable, innovative and enterprising, Biculturally Competent and Confident (kaupapa 1, 3, 5)

    5.Ability to use R to process and analyze data (assessment: lab quizzes, final exam)
    Related Graduate Attributes and Kaupapa: Critically competent in the core academic discipline, Employable, innovative and enterprising

    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 everyday life. (assessment: lab quizzes, final exam)
    Related Graduate Attributes and Kaupapa: Critically competent in the core academic discipline, Employable, innovative and enterprising
  • Ability to apply basic concepts in exploratory data analysis. This ability is important for distinguishing between different types of data, methods of summarising data both graphically and through summary statistics. (assessment: lab quizzes, midterm test, final exam)
    Related Graduate Attributes and Kaupapa: Critically competent in the core academic discipline, Employable, innovative and enterprising
  • Knowledge of the basics of collecting data and generating descriptive statistics. This skill is essential for all higher-level courses that include laboratory or field based research activities. (assessment: lab quizzes, midterm test, final exam)
    Related Graduate Attributes and Kaupapa: Critically competent in the core academic discipline
  • Ability to apply the appropriate test and draw appropriate conclusions from the test output. This ability is important aspect of research and its application. (assessment: lab quizzes, final exam)
    Related Graduate Attributes and Kaupapa: Critically competent in the core academic discipline, Employable, innovative and enterprising
  • 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. (assessment: lab quizzes, final exam)
    Related Graduate Attributes and Kaupapa: Critically competent in the core academic discipline, Employable, innovative and enterprising

Pre-requisites

STAT101 or
15 points of 100 level MATH

Timetable 2021

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Monday 09:00 - 10:00 A2 Lecture Theatre
22 Feb - 4 Apr
3 May - 6 Jun
Lecture B
Activity Day Time Location Weeks
01 Friday 13:00 - 14:00 C2 Lecture Theatre
22 Feb - 28 Mar
26 Apr - 6 Jun
Computer Lab A
Activity Day Time Location Weeks
01 Tuesday 13:00 - 15:00 Jack Erskine 001 Computer Lab
8 Mar - 4 Apr
26 Apr - 6 Jun
02 Tuesday 08:00 - 10:00 Jack Erskine 001 Computer Lab
8 Mar - 4 Apr
26 Apr - 6 Jun
03-P1 Monday 11:00 - 13:00 Jack Erskine 001 Computer Lab
8 Mar - 4 Apr
3 May - 6 Jun
03-P2 Thursday 17:00 - 19:00 Ernest Rutherford 464 Computer Lab
26 Apr - 2 May
Computer Lab B
Activity Day Time Location Weeks
01 Wednesday 16:00 - 17:00 Ernest Rutherford 212 Computer Lab
22 Feb - 7 Mar
02 Thursday 11:00 - 12:00 Ernest Rutherford 212 Computer Lab
22 Feb - 7 Mar
03 Thursday 10:00 - 11:00 Ernest Rutherford 212 Computer Lab
22 Feb - 7 Mar
04 Thursday 12:00 - 13:00 Ernest Rutherford 212 Computer Lab
22 Feb - 7 Mar
05 Tuesday 09:00 - 10:00 Ernest Rutherford 212 Computer Lab
22 Feb - 7 Mar
06 Thursday 09:00 - 10:00 Ernest Rutherford 212 Computer Lab
22 Feb - 7 Mar
Tutorial A
Activity Day Time Location Weeks
01 Wednesday 12:00 - 13:00 C3 Lecture Theatre
1 Mar - 4 Apr
26 Apr - 6 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 Sarah Flanagan 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

Sarah Flanagan

Lecturers

Daniel Stouffer and David Schiel

Assessment

Assessment Due Date Percentage 
Final Exam 50%
Lab quizzes 20%
Mid term Test 30%

Textbooks / Resources

Recommended Reading

Crawley, Michael J; Statistics : an introduction using R ; Second edition; John Wiley & Sons, Inc., 2014.

Course links

Course Outline

Indicative Fees

Domestic fee $910.00

International fee $4,438.00

* 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 School of Biological Sciences .

All BIOL209 Occurrences

  • BIOL209-21S1 (C) Semester One 2021