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: 10:00 am to 12:00 pm
- Session Two: 12:30 pm to 1:30 pm (students can pop in to zoom and ask for assistance)
- Lunch time 1:30 pm to 2:30 pm
- Session Three: 2:30pm to 4:30pm
- Session Four : 5:00pm to 6:00pm (Monday & Tuesday only - students can pop in to zoom and ask for assistance)
This course is being held online via Zoom and run on Australian Eastern Standard Time (UTC +10)
This course is now FULL.
We are offering a 2nd Fundamentals of Statistics: Online course from July 11-15.
You can enrol by following this link.
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, 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, confidence intervals and effect size statistics.
Day 4
- t- tests
- Single sample t-test, paired samples t-test, independent sample t-test
- confidence intervals, effect size statistic, Cohen's d, testing of assumptions, report writing and journal article examples.
Day 5
- Relationship between power, effect size, sample size, type 1 and 2 errors.
- Introduction to GPower for determining the sample size required to achieve a given level of power for studies involving independent samples t-tests
- Chi-square test
- Hypothesis tests, effect size statistics, testing of assumptions, report writing and journal article examples
- Inference for Pearson Correlation
- Choosing the correct statistical test
Training in this course will be over ZOOM using your own computer and internet connection.
Session One: 10:00 am to 12:00 pm
Session Two: 12:30 pm to 1:30 pm (students can pop in to zoom and ask for assistance)
Lunch time 1:30 pm to 2:30 pm
Session Three: 2:30pm to 4:30pm
*Session Four: 5:00pm to 6:00pm (*Monday and Tuesday only)
There are no prerequisites for this course, nor is previous computing experience with SPSS 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 your nominated 'shipping' address 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.
The balance of content, application and breaks was spot on. It made the course accessible and it wasn't overwhelming.
The structure of the course was fantastic. Imma made it easy for everyone to ask questions and to clarify, but when the exercises got a little bit tricky, the ability to go to the breakout room with Debbie and to talk through the process was excellent. I wasn't quite at the same level of confidence as other people in the main group, but the smaller group in the breakout room was a safe space to slow things down, ask more questions (and not slow others down!). Just brilliant! Thank you!
Imma had a very good balance of theoretical content and practice opportunities. She also had good revision activities (polls).
Learning online was great. I found it just as good as face to face. I think it was because the teacher, Imma was clear and kept very close to time and ran the course very well.
I thought it may be more difficult to do the course on-line, but the tutor was excellent, the pace was not too fast for a novice and there were plenty of opportunities to practise and ask questions.
I came in with no knowledge of statistics at all and a history of thinking myself unable to do any math - Imma was fabulous in explaining everything and gave me the confidence to work with stats.
I’ve always found statistics to be difficult abstact and confusing. I had many aha moments with Imma - she’s a great teacher.
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.
Went through each topic well with a great balance of theory/ lecture / practical / demonstration and practise labs and computer use.
Coming from a non stats background! I have gained a very informed intro to stats.
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
I will be more literate in reading literature drawing on statistics in myfield as well as able to apply some of the techniques myself.
The instructor's bound, book length course notes will serve as the course text.