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# STA420 Scientific Statistics (8)

### Abstract

 This subject provides a foundation in the basic practice of statistics, ie explaining variability. The orientation is towards the sciences covering both experimental and observational data. The emphasis is on understanding statistical concepts and applying acquired skills to data interpretation by the use of modern software packages. The modern approach to the teaching of statistics is used including group work, use of local data and small projects.

### + Subject Availability Modes and Location

 Continuing students should consult the SAL for current offering details prior to contacting their course coordinator: STA420 Where differences exist between the handbook and the SAL, the SAL should be taken as containing the correct subject offering details.

### Subject information

One sessionHD/FLSchool of Science and Technology

### Learning Outcomes

 Upon successful completion of this subject, students should: Be able to use graphical and numerical methods to describe both quantitative and qualitative data;Be able to interpret and explain graphical and numerical summaries using statistical language;Be able to use a modern calculator and a statistical software package;Be able to identify the appropriate statistical techniques and conduct statistical analysis (both by hand and with the use of a computer);Be able to interpret computer output from analyses and reproduce such calculations manually;Be able to explain the relationship between probability, statistics and inference;Be able to demonstrate an understanding of the assumptions underlying statistical techniques;Be able to understand the importance of experimental design in terms of inference, sample size, cost and efficiency.

### 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; Random Variables: Representing the outcome of experiments in terms of random variables, distinguishing between discrete and continuous random variables and calculating probabilities; 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, controlled experimentation, randomisation and causality, distribution of sample means and proportions, confidence intervals, hypothesis tests; Inference based on two independent samples: Using a sample to gain information about a population, controlled experimentation, randomisation and causality, distribution of sample means and 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: Fitting distributions to data, checking distributions graphically and by chi-square, testing 2-way tables of counts; Regression: Intercept and slope, error sum of squares, correlation, relation to slope, F and t tests of slope, R squared; Experimental Design: Difference between experimental and observational data, issues of cost, sample size, efficiency, layout of simple orthogonal designs - single factor, randomised blocks, latin square, balanced incomplete block, factorial designs.

### Residential School

 This subject contains a optional 3 day residential school.

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The information contained in the 2016 CSU Handbook was accurate at the date of publication: 06 September 2016. The University reserves the right to vary the information at any time without notice.