Use the Tab and Up, Down arrow keys to select menu items.
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 andinterpretation 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.
As a student in this course, I will develop the ability to:Learning Outcome Number 1 (LO1)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 enterprisingLearning Outcome Number 2 (LO2)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 enterprisingLearning Outcome Number 3 (LO3)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 enterprisingLearning Outcome Number 4 (LO4)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)Learning Outcome Number 5 (LO5)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 enterprisingPūkenga ngaio | Transferable skillsAs 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 enterprisingAbility 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 enterprisingKnowledge 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 disciplineAbility 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 enterprisingInterpretation 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
STAT101 or 15 points of 100 level MATH
Students must attend one activity from each section.
Feedback from previous Course SurveysThe course has not had a proper course survey in the last couple of years (we hope to this year), but last year we received feedback in other formats. Please see Course Outline for full details.Course contact: biology209@canterbury.ac.nz
Sarah Flanagan
Whitlock, Michael , Schluter, Dolph; The analysis of biological data ; Third edition; Macmillan Learning, 2020.
This is available from the University Bookshop, Amazon, FishPond, Booktopia, and other book sellers. It can also be accessed via the library on either a 3-day or 3-hour loan.We think this is the best statistics textbook available for biology students at a 200-level, and it has additional highly valuable resources including practice problems with answers. So, if it is within your means, we really do recommend obtaining a copy of this book for your personal library, even though this is only the recommended book, as you will find it useful when you return to these concepts in future coursework.
Course Outline
Domestic fee $1,036.00
International fee $5,188.00
* 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 .