Fundamentals of Statistics: Online

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
  • Lunch time 1:30 pm to 2:30 pm
  • Session Three: 2:30pm to 4:30pm

 

 

This course is also being held online via Zoom and run on Australian Eastern Daylight Time (UTC +11)

(Canberra, Sydney, Melbourne Daylight Savings time)

 

 

This course is being offered in person at the University of Melbourne from Jan 30 - Feb 3

You can visit the course page by following this link

 

 

 
Level 1 - runs over 5 days
Course dates: Monday 16 January 2023 - Friday 20 January 2023
Instructor: 

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.

Venue: 
Online
Week: 
Week 1
About this course: 

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. Key examples from journal articles will be presented to illustrate the use and reporting of the statistical techniques covered in this unit.

 

Our approach to learning will be largely non-mathematical, concentrating on concepts rather than mathematical theory. Participants familiar with the use of a statistical software package, but lacking statistical training should also start with this course.

 

SOFTWARE

The course will be using the free and open-source software jamovi. The software jamovi can be downloaded from https://www.jamovi.org.download.html

While jamovi is built on top of the R statistical language, it has a look and feel very similar to IBM SPSS Statistics and in many ways is easier to use.

Depending on student preferences, there will be an opportunity to use IBM SPSS Statistics v28. Instructions will be provided for both packages and students can choose either jamovi or IBM Statistics v28.

 

Course syllabus: 

Day 1

  • Level of measurement of data
  • Descriptive statistics and graphs for a single variable
    • Histogram, stemplot, boxplot, bar chart, frequency tables
    • Mean, median, mode, std deviation, quartiles, range, outliers

 

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, including how to test normality assumption.

 

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 correlation and regression
  • Choosing the correct statistical test

 

Course format: 

Training in this course will be over ZOOM using your own computer and internet connection.

 

This course will be run over 5 days in the following sessions each day:

  • 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
     
Recommended Background: 

There are no prerequisites for this course, nor is previous computing experience with IBM SPSS Statistics V28 or jamovi necessary.

 

Recommended Texts: 

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.

Detailed instructions will also be provided for how to obtain the statistical output from both jamovi and IBM SPSS v28

 

Course notes will be sent to your nominated 'shipping' address in advance.

 

Course fees
Early bird Member: 
$1,680
Early bird Non Member: 
$3,280
Early bird full time student Member: 
$980
Member: 
$2,100
Non Member: 
$3,650
Full time student Member: 
$1,800
FAQ: 

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.

Participant feedback: 

Extremely useful for higher degree research as a beginning step.

 

It provided an excellent understanding of the underlying principles of statistics that helped understand the techniques taught as well as underpinning of future statistical techniques.

 

The workbooks were great and the tasks were well connected to the coursework and these workbooks. It felt like there was a great balance between doing activities ourselves and the teacher-led sessions.

 

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.

 

Coming from a non stats background! I have gained a very informed intro to stats.

 

 

I will be more literate in reading literature drawing on statistics in myfield as well as able to apply some of the techniques myself.

 

 

Program: 
Summer Program 2023
Notes: 

The instructor's bound, book length course notes will serve as the course text.