STA401 Postgraduate Scientific Statistics (8)
CSU Discipline Area: Mathematics and Statistics (MASTA)
Duration: One session
Abstract:
This subject provides a foundation in the basic practice of statistics, i.e. making decisions in the presence of variability. The orientation is towards the sciences and covers both experimental and observational data. The emphasis is on understanding statistical concepts and applying acquired skills to data interpretation by the use of a modern software package.
+ Subject Availability Modes and Locations
| Session 1 | |
|---|---|
| Distance * | Wagga Wagga | Session 2 |
| Distance * | Wagga Wagga |
*This subject offering contains a residential school. Please view following information for further details.
Continuing students should consult the SAL for current offering details: STA401
Where differences exist between the Handbook and the SAL, the SAL should be taken as containing the correct subject offering details.
Enrolment restrictions:
Students who have completed QBM117 or QBM217 or STA109 or STA117 or STA201 may not enrol in STA401 . This is because a significant component of material covered in STA401 is similar to material they have already studied in these other subjects.
Objectives:
Upon successful completion of this subject, students should:
- Be able to explain standard uses of Statistics in the media and in scientific papers, and judge whether the statistical methodology and conclusions drawn are appropriate;
- Be able to summarise and interpret data graphically and numerically;
- Be able to calculate and interpret probabilities, and use standard discrete and continuous probability distributions;
- Be able to explain the concepts of statistical inference, and apply these to confidence intervals and tests of hypotheses;
- Be able to use a statistical package to analyse data appropriately, and then interpret the output;
- Be able to evaluate if the assumptions underlying statistical techniques are valid in a given scenario;
- Be able to apply basic principles of experimental design, such as determination of appropriate sample sizes, randomisation and blocking; and
- Be able to interpret a scientific problem and develop a statistical solution to that problem.
Syllabus:
The subject will cover the following topics:
- Descriptive statistics: Graphs and statistics as summaries, frequency tables, concept of population and sample, random variation, measurement levels (categorical, ordinal, interval, ratio), measures of location and dispersion, mean and median, standard deviation, range and coefficient of variation;
- Basic probability: Probability estimate from relative frequency and percentiles, conditional probability;
- Random variables: Representing the outcome of experiments in terms of random variables, distinguishing between discrete and continuous random variables, calculating probabilities using the Binomial, Poisson and Normal distributions;
- Sampling distributions: The application of various sampling strategies and the distribution of sample means and proportions;
- Inference based on a single sample: Using a sample to gain information about a population, distribution of sample means and proportions, confidence intervals, hypothesis tests;
- Inference based on two independent samples: Using samples to gain information about populations, controlled experimentation, distribution of differences in sample means or proportions, confidence intervals, hypothesis tests;
- Analysis of variance: One-way ANOVA for testing differences in two or more means, graphical displays, checks on assumptions and post hoc tests;
- Chi-square tests: Testing whether data fit a specified distribution, checking distributions graphically, and testing for independence of two categorical variables;
- Simple linear regression and correlation: Estimating the intercept and slope of the Least Squares line, testing the slope of the regression line, interpreting coefficient of determination (R squared) and correlation; and
- Experimental design: Difference between experimental and observational data, randomisation, causality, replication, blocking and sample size.
Residential School
This subject contains a optional 2 day residential school.
Lecture/workshop sessions
The information contained in the 2013 CSU Handbook was accurate at the date of publication: 24 April 2013. The University reserves the right to vary the information at any time without notice.