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Summer School details

  • Lecturer: Aaron Bryant
  • Lectures: 10:00 Monday to Thursday
  • Tutorials: 12:00, 13:00 and 14:00 Tuesday and Thursday
  • There will be 7 marked assignments and 3 tests





A researcher is interested in whether men are more or less likely than women to exercise. A random sample of 90 men and 80 women are surveyed on whether they exercise or not. Of the 90 men, 74 exercise; of the 80 women, 54 exercise. Is there evidence of a difference in the proportion of men and women who exercise?




A psychologist, assisting with the trialling of road signs, is recording motorists’ recall of information. A random sample of 20 motorists were stopped after travelling 1 km beyond one particular sign. Let X be the random variable for the number of motorists who correctly recall the information. What are the conditions necessary for X to be from the binomial distribution?




Sir Ronald Aylmer Fisher (1890-1962) was one of the founders of modern statistics because of his many important contributions. He worked at the Rothamsted Agricultural Experiment Station in England and made many important contributions to genetics as well as statistics.

Amongst his achievements are:
  • the concept of randomisation and analysis of variance, procedures now used throughout the scientific world;
  • the concept of likelihood: the likelihood of a parameter is proportional to the probability of the data and it gives a function which usually has a single maximum value, which he called the maximum likelihood;
  • the development of methods suitable for small samples;
  • the discovery of the precise sampling distributions of many statistics.

STAT110 Statistical Methods

First Semester, Summer School, 18 points
What is the biomass of cockles at Papanui Inlet?
What do overseas tourists come to New Zealand to see?
Are Hector and Maui dolphins different species?
Investigating survival of a rare bird
Is circumcision protective against HIV/AIDS?
Are Dunedin residents in favour of a new harbourside stadium?
Identifying sleep problems at high altitude
Are there pain effects when removing horns of young cattle?

These questions are typical of those posed by scientists working in the biological sciences, life sciences and social sciences. A grounding of statistics and probability is crucial for both carrying out scientific research and understanding the scientific literature.

Paper details

This is a paper in statistical methods for students from the sciences, including students studying biological science, social sciences, and sport science as well as those studying mathematics and statistics. The paper covers data, an introduction to probability, binomial and normal distributions, estimation, hypothesis testing, contingency tables for categorical data, simple linear regression, introduction to multiple regression, analysis of variance. At the end of the course you should be able to make use of a wide variety of techniques in the design and analyse your own research studies.

Potential students

This course is intended for students who need to use statistical methods in the other courses, as well as those interested in specializing in statistics and mathematics.

Main topics

  • Data: where does it come from and how should we collect it?
  • Probability
  • Binomial and normal distributions
  • Sampling distributions
  • Confidence Intervals and estimation
  • Hypothesis testing and power
  • Contingency tables for categorical data
  • Analysis of variance
  • Regression including simple linear and multiple linear with confounding discussion.

Prerequisites

None

Required text

None.
(Semester 1 and Summer School) Course materials including copies of slides from lectures will be available on the resource page.
A book of complete notes is available for purchase from Uniprint.

References

Clark, M.J. and Randal, J. R. A First Course in Applied Statistics. Pearson

MacGillivray, H. Utts & Heckard's Mind on Statistics. Cengage Learning.

Multiple copies of both references are in the Science Library on close reserve at the Loans Desk.

Lecturers

(Summer School) Aaron Bryant, Math/Stat Annexe, 539 Castle Street

Lectures

(Summer School) 4 lectures per week: Monday, Tuesday, Wednesday, Thursday 10am-12am at Quad 2

Tutorials

(Summer School) 2 Tutorial times per week: Tuesday and Thursday 1pm - 5 pm at 539 Castle Street. Tutorials will begin in the first week of lectures, starting Tuesday 10th January. Tutorials will be cafeteria style, students are free to attend at any time.

Internal Assessment


(Summer School) There will be seven assignments during the semester. All assignments will have equal weighting. The assignments contribute 1/3 of your internal mark.
There will be 3 mastery tests during the semester, these must be taken in the Tutorial room under test conditions. 2 attempts will be allowed but the 2nd attempt will count if a re-sit is taken. The mastery tests contribute 2/3 of your internal mark.

Exam format

The final exam lasts 3 hours and about half will be multiple choice with the rest written including calculations.

Final mark

The final mark F is calculated from:
F = max { E, (2E + A)/3 }
where E (exam mark) is out of 100, A (internal assessment) is out of 100.

The “max” corresponds to plussage: if your internal assessment mark is greater than your exam mark then it is combined in the proportion shown. If it is less then it is ignored and the exam mark itself is used.


Plagiarism

Students should make sure that all submitted work is their own. “Plagiarism is a form of dishonest practice. Plagiarism is defined as copying or paraphrasing another’s work and presenting it as one’s own” (University of Otago Calendar). In practice this means that plagiarism includes any attempt in any piece of submitted work (e.g. an assignment or test) to present as one’s own work the work of another (whether of another student or a published authority). Any student found to be responsible for plagiarism in any piece of work submitted for assessment shall be subject to the University’s dishonest practice regulations which may result in various penalties, including forfeiture of marks for the piece of work submitted, a zero grade for the paper, or in extreme cases exclusion from the University. The University of Otago reserves the right to use plagiarism detection tools.

While we strive to keep details as accurate and up-to-date as possible, information given here should be regarded as provisional. Individual lecturers will confirm teaching and assessment methods.