Note: while this course is focussed on statistical theory and tehniques, rather than how to use a particular software, all examples and demonstrations on this occasion will be carried using SPSS. If you would prefer examples to be done using STATA, please refer to the same course in Week 1 (in Canberra).
Note also: A laptop with SPSS installed will be required for this course. If you have difficulty obtaining a laptop or accessing an SPSS license for the duration of the course, please contact us at info@acspri.org.au.
The approach will be largely non-mathematical, concentrating on concepts rather than mathematical theory. The first part of the course is an introduction to descriptive statistics for univariate and bivariate data, covering topics such as frequency tables, histograms and stemplots, the median, IQR & boxplots, the mean & standard deviation, levels of measurement, scatterplots, Pearson's r, introduction to regression, relationships in tabulated data, correlation and causality.
The second part of the course deals with the ideas of inferential statistics. Topics covered include a basic discussion of experimental design and sampling procedures, followed by the normal distribution, sampling distributions, hypothesis testing and confidence interval for the proportion, hypothesis test for the correlation coefficient, t-tests for paired and independent data and also the one sample t-test, including effect size statistics for the t tests, the chi-squared test, and confidence intervals for the mean. The statistical package SPSS will be used where appropriate as a teaching tool and computational aid (previous experience is not assumed). Students will be able to gain competency in using SPSS to obtain all the graphs and statistics covered in the course.
The overall focus of the course is for students to obtain a solid foundation of basic statistical concepts and procedures in order for students to then progress with some confidence into more advanced topics.
Imma Guarnieri [BSc, Grad DipEd, Grad Dip Applied Science (Social Statistics), Masters of Biostatistics] is a Lecturer in Clinical Research in the Department of Medical Education at the University of Melbourne. She has been involved in teaching Statistics to postgraduate students for over 20 years.
None; nor is previous computing experience necessary.
The instructor's bound, book length course notes will serve as the course text. The notes contain detailed explanations and examples of all the statistical concepts covered along with instructions of how to obtain the various graphs and statistics from Stata.
Participants will receive a copy of the course notes on the first day.