This is an introductory unit in statistical methods with the emphasis on statistical techniques applicable to the social sciences, although these introductory techniques are also relevant to the health sciences.
This course will be run over 5 days:
Session One: 9:00 am to 11:00 am
Practice time: 11:30 am to 12:30 pm (students can pop in to zoom and ask for assistance)
Lunch time 12:30 pm -1:30 pm
Session Two: 1:30pm to 3:30pm
Practice time : 4:00pm to 5:00pm (students can pop in to zoom and ask for assistance)
Imma Guarnieri [BSc, Grad DipEd, Grad Dip Applied Science (Social Statistics), Masters of Biostatistics] is a sessional lecturer in the School of Health Sciences at Swinburne University of Technology and in Medical Education at the University of Melbourne. She has been involved in teaching Statistics to postgraduate students for the past 20 years.
In this course you will obtain a solid foundation in basic statistical concepts and procedures to progress with some confidence into more advanced topics. This is an introductory unit in statistical methods with the emphasis on statistical techniques applicable to the social sciences, although these introductory techniques are also appropriate to the health sciences.
Our approach to learning will be largely non-mathematical, concentrating on concepts rather than mathematical theory.
Participants familiar with the use of a package, but lacking statistical training should also start with this course. The statistical package SPSS will be used where appropriate as a teaching tool and computational aid, (previous experience is not assumed). You will be able to gain competency in using SPSS to obtain all the graphs and statistics covered in the course.
Day 1
- Level of measurement of data
- Introduction to SPSS
- Descriptive statistics and graphs for a single variable
- Histogram, stemplot, boxplot, bar chart, pie chart, frequency tables
- Mean, median, mode, std deviation, quartiles, range, outliers
- Descriptive statistics and graphs for a single variable
Day 2
- Descriptive statistics for relationships between two variables
- Comparative boxplots, scatterplots, contingency tables, clustered and stacked bar charts.
- Introduction to correlation and regression.
Day 3
- Foundations of basic inference and confidence intervals.
- Normal Distribution, standardisation
- Sampling distribution of the mean
- Introduction to hypothesis testing and confidence intervals
- One sample t-test and z-test for a single mean, including
- confidence intervals, effect size statistic, Cohen's d, testing of assumptions, report writing and journal article examples.
Day 4
- Paired and independent samples t-test
- confidence intervals, effect size statistic, Cohen's d, testing of assumptions, report writing and journal article examples.
- Introduction to GPower for determining the sample size required to achieve a given level of power for studies involving independent samples t-tests
Day 5
- Chi-square test & Inference for correlation and regression
- Hypothesis tests, confidence intervals, effect size statistics, testing of assumptions, report writing and journal article examples
- Choosing the correct statistical test
Training in this course will be over ZOOM using your own computer and internet connection.
Session One: 9:00 am to 11:00 am
Practice time: 11:30 am to 12:30 pm (students can pop in to zoom and ask for assistance)
Lunch time 12:30 pm -1:30 pm
Session Two: 1:30pm to 3:30pm
Practice time : 4:00pm to 5:00pm (students can pop in to zoom and ask for assistance)
There are no prerequisites for this course, 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 SPSS.
Course notes will be sent to you in advance.
Q. Do I have to know any statistics to do this course?
A. No, there are no prerequisties and you don't need any computing experience.
Most of the course was taught through speaking and presentation with the back up of course notes, then hands on work in SPSS and the exercises were very helpful to ensure we understand the concept. (Winter 2019)
I’ve always found statistics to be difficult abstact and confusing. I had many aha moments with Imma - she’s a great teacher. (Winter 2019)
It provided fundamental thinking & reasoning behind concepts I see at work such as confidence intervals & involved some maths - which makes me want to learn more. (Summer 2019)
Went through each topic well with a great balance of theory/ lecture / practical / demonstration and practise labs and computer use. (Spring 2018)
Coming from a non stats background! I have gained a very informed intro to stats. (Summer 2018)
Using SPSS to analyses my data,learnt & consolidated methods. Love the course, learnt so much can’t wait to get home and look at my work (Winter 2017)
I will be more literate in reading literature drawing on statistics in myfield as well as able to apply some of the techniques myself. (Summer 2017)
very well balanced. Loved the activity book with step-by-step notes. (Spring 2016)
I have learnt so many basic concepts that I have been expected to understand. To have the opportunity to learn them is fantastic. (Winter 2016)
The instructor's bound, book length course notes will serve as the course text.