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
(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 Daylight Time (GMT +11)

 

 

This course is now FULL

Please leave your name on the waiting list, so we can contact you if a place becomes available

 

 
Level 1 - runs over 5 days
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.

Course dates: Monday 17 January 2022 - Friday 21 January 2022
Course status: Course completed (no new applicants)
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.

 

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.

Course syllabus: 

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

 

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

 

Course format: 

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) 

Recommended Background: 

There are no prerequisites for this course, nor is previous computing experience with SPSS 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 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.

 

Course fees
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: 

Imma had a very good balance of theoretical content and practice opportunities. She also had good revision activities (polls). (Winter Online 2021)

 

The course was great. It provided a good mix of guided learning and independent activities. (Summer Online 2021)

 

Excellent balance of theory, work examples and practice. (Summer Online 2021)

 

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. (Online Winter 2020)

 

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. (Online Winter 2020)

 

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. (Online Winter 2020)

 

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)

 

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)

 

 

 

Notes: 

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