This subject provides a foundation in the basic practice of statistics, i.e. making decisions in the presence of variability. The focus is on data seen in typical business situations. The emphasis is on understanding statistical concepts and applying acquired skills to data interpretation by the use of a modern software package.

Session 2 (60)

On Campus

Albury-Wodonga Campus

Bathurst Campus

CSU Study Centre Melbourne

CSU Study Centre Sydney

Port Macquarie Campus

Wagga Wagga Campus

Online

Wagga Wagga Campus

Session 3 (90)

Online

Wagga Wagga Campus

HD/FL

One session

School of Computing and Mathematics

Not available to students who have completed STA109 or STA117. STA117 was identical in content to QBM117 but was taken by students in the Industrial Maths degree rather than a business degree. It has not existed for 10 years or more. STA109 had similar content to QBM117 and was taught in Bachelor of Environmental Science Management course taught out of Albury. It also no longer exists.

STA201 75% overlap

MTH135 50% overlap

STA117 now obsolete

STA401 75% overlap

STA109 now obsolete

STA109, STA117

- be able to explain the standard uses of Statistics in the media and in business environments, 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 survey design, such as determination of appropriate sample sizes and sampling techniques.

- 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;
- 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.

*The information contained in the CSU Handbook was accurate at the date of publication: January 2020. The University reserves the right to vary the information at any time without notice.*