Fundamentals of Statistics

This is an introductory unit in statistical methods with the emphasis on statistical techniques applicable to the social sciences.

 

 

 

 
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 24 June 2019 - Friday 28 June 2019
Course status: Course completed (no new applicants)
Week: 
Week 1
About this course: 

In this course you will obtain a solid foundation in basic statistical concepts and procedures in order 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.

 

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 for a single variable including summary statistics, graphs, writing brief summary reports

                     - Histogram, stemplot, boxplot, bar chart, pie chart, frequency tables
                     - Mean, median, mode, std deviation, quartiles, range, outliers

 

Day 2

  • Descriptive statistics for relationships between two variables

                     - Comparative boxplots, scatterplots, introduction to correlation and regression, contingency tables, clustered and stacked bar charts

  • Causation, association, lurking variables,

 

Day 3

  • Foundations of basic inference and confidence intervals.

                    - Normal Distribution, standardization
                    - Sampling distribution of the mean and the proportion

 

Day 4

  • Hypothesis tests, confidence intervals, effect size statistics, testing of assumptions,  report writing and journal article examples for the following

                    - Single proportion, single mean (z-test and one sample t-test)

  • Relationship between confidence intervals and hypothesis test, type 1 and type 2 errors

 

Day 5

  • Hypothesis tests, confidence intervals, effect size statistics, testing of assumptions,  report writing and journal article examples for the following

                    - Paired and Independent samples t-tests, Pearson’s correlation and chi-square

  • Choosing the correct statistical test
Course format: 

This course may run in a computer lab, or you may be advised to bring your own laptop with specified software.

We will let you know in advance.

Recommended Background: 

There are no prerequisites for this course, nor is previous computing experience 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 fees
Member: 
$2,250
Non Member: 
$3,900
Full time student Member: 
$1,980
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: 

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)

 

Imma’s use of examples to explain concepts was outstanding. Being able to try out techniques after they are discussed was great. (Winter 2015)

 

Program: 
Winter Program 2019
Notes: 

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