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.

## Availability

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

Continuing students should consult the SAL for current offering details: QBM117. Where differences exist between the Handbook and the SAL, the SAL should be taken as containing the correct subject offering details.

## Subject Information

HD/FL

One session

##### School

School of Computing and Mathematics

##### Enrolment Restrictions

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.

##### Subject Relationships

STA201 75% overlap
MTH135 50% overlap
STA117 now obsolete
STA401 75% overlap
STA109 now obsolete

STA109, STA117

## Learning Outcomes

##### Upon successful completion of this subject, students should:
• 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.

## Syllabus

##### This 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;
• 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.