Stage 2 Courses

Stage 2 Courses in Statistics

We teach four different aspects of Statistics at Stage 2, namely Data Analysis (STATS 201 or STATS 208), Statistical Theory (STATS 210), Statistical Computing (STATS 220) and Operations Research (STATS 255). If you wish to advance in Statistics you are advised to take at least the first two of these courses (ie. take one of STATS 201/8 and also STATS 210). They are prerequisites for some of the Stage III courses and STATS 210 is a prerequisite for all postgraduate courses.

STATS 201 Data Analysis

The courses STATS 201/8 teach computer based data analysis. They are particularly useful for Business and Economics, and the Biological, Medical and Social Sciences. They are useful for anyone who will do research, or even just read research papers in any discipline where research makes use of statistical analyses.

Topics studied include: Exploratory Data Analysis, Review of Statistical Inference, Tables of Counts, Models and Transformations, Regression, Analysis of Varience, Logistic Progression and Time Series.

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STATS 207 Data-centered Investigation and Analysis

A practical course in the statistical analysis of data, with hands on experience in research design and execution. The primary coursework assessment will be a self-selected group project. STATS 207 will have shorter assignments than STATS 201/208 and no mid-semester test. The exam for STATS 207 will be the same as for STATS 201/208.

Topics studied include: Exploratory Data Analysis, Review of Statistical Inference, Tables of Counts, Models and Transformations, Regression, Analysis of Varience, Logistic Progression and Time Series.

*Please ignore the STATS 207 course details in the Handbook, this website has the most updated information on STATS 207.

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STATS 208 Data Analysis for Commerce

Refer to STATS 201 for further details.

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BIOSCI 209 Biometry

This course is designed to provide biology students with an introduction to basic statistics and data analysis. Emphasis is placed on conceptual understanding of topics and interpretations of results. The course uses the computer software JMP.

Topics studied include:

1. Random variables, displaying data and summary statistics
2. Probability, conditional probability and independence
3. Statistical distributions: the binomial, the Poisson and the normal
4. Statistical inference, Central limit theorem, confidence intervals for means, the t-distribution
5. Hypothesis testing, one-sample and two-sample t-tests, errors and power
6. Correlation and the relationship between two variables
7. Regression, a linear predictive model and transformations
8. Analysis of variance (ANOVA), comparing means among groups
9. Two-way ANOVA, main effects and interactions
10. Analysing frequencies, chi-squared, one-way and two-way tables of counts

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STATS 210 Statistical Theory

STATS 210 introduces the theory that underlies the statistical methods used in practical statistics courses. It is aimed at students who enjoy maths and are interested in probability and statistics. It is useful for students with interests in Econometrics, Operations Research, Finance, and theoretical aspects of Marketing Research, as well as those who have Maths or Statistics as their main interest. STATS 210 is a prerequisite for STATS 310 and admission to a Postgraduate degree in Statistics. Student majoring in Statistics must take either STATS 125 or STATS 210.

Topics studied include: Probability, random variables, discrete and continuous probability distributions, likelihood and hypothesis tests.

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STATS 220 Data Technologies

This course introduces a variety of computer technologies relevant to gathering, managing, and processing data. The course has two aims: to teach software tools specific to the handling of data, and to teach and build confidence with general concepts of computer languages. It is useful for students with interests in applying statistics in business or research environments. Lectures will be reinforced with weekly (optional) lab work.

Topics studied include: How to Write Computer Code; Publishing Data on the World-Wide Web (HTML); Data Description and Semantic Markup (XML); Data Storage (File Formats, Spreadsheets, Databases); Data Management and Summary (Database Queries, SQL); Data Processing (Scripting, Pattern Matching, R).

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STATS 255 Introduction to Operations Research

STATS 255 considers a range of practical operations research problems, including effective use of limited or valuable resources such as machines and personnel, understanding queues and simulation. The course is valuable for students interested in Commerce, Statistics, Mathematics, and Computer Science.
STATS 255 will emphasise the relationship between business and industrial applications and their associated Operations Research models. Computer packages will be used to solve practical problems.

Topics studied include: Linear programming, transportation and assignment models, network algorithms, queues, inventory models, and simulation.

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