This course is designed for researchers and students looking to design their research studies and analyse / interpret the findings. The emphasis is placed on achieving the highest calibre results to answer specific research questions common to quantitative research.
Dr Minh Huynh is the Major Discipline Coordinator (Applied Statistics) at Swinburne University where his principle duties include curriculum design / implementation and quality control / evaluation for all units within the Applied Statistics Major. He is also involved with teaching intensive statistics courses at different international locations, which focus on delivering content to students who are not fluent with English. His primary area of research is focused on statistics education and teaching statistics, where he presents at both national and international conferences. In doing so, Minh has been able to transfer the knowledge and skills from his research, into pedagogical practices for his teaching.
This course will introduce you to experiments and quasi-experiments in the social sciences. The emphasis is on designing experimental studies to achieve the highest calibre results to answer specific research questions common to quantitative research. Additionally, you will be introduced to the statistical analyses necessary for the data generated from an experimental design. This particular course will also explain how to conduct the necessary analyses using SPSS.
Following from a brief review of introductory statistics, the nature of experiments and causal inference will be discussed. This will include a discussion of common threats to validity and methods to assess the quality of the experimental (or quasi-experimental) design. Along with discussing true and quasi-experiments, this course will also address issues related to multiple regression. The focus will be on the types of research questions that can be answered with multiple regression analysis, and how these forms of observational/correlational studies are distinct from true experiments. Specific statistical analyses will be introduced, including 1-way, 2-way and factorial ANOVA; multiple comparison protocols for post hoc analyses; multiple regression for continuous and categorical predictors; ANCOVA; repeated measures ANOVA; mixed ANOVA designs; and hierarchical (nested) designs.
This course is designed for researchers who want to design experiments that provide generalizable findings. It is ideal for post-graduate students who are preparing proposal or programs of study for their degree. It is also ideal for professional researchers who want to increase their quantitative analysis research skill set.
Day 1
a. Review of introductory statistics
b. Causation and Experiments (and quasi-experiments)
c. The Linear Model: Multiple Regression
d. Using SPSS to fit a linear model with several predictors
Day 2
a. Comparing two means: Review of the t-test
b. Comparing several independent means: Introducing the General Linear Model & ANOVA
c. Multiple comparisons (planned vs. post hoc)
d. Using SPSS to analyse and interpret one-way independent ANOVA
Day 3
a. Threats to validity & statistical bias
b. Comparing means adjusted for other predictors: ANCOVA
c. Factorial Designs
d. Using SPSS to analyse and interpret Factorial ANOVAs
Day 4
a. Repeated Measures Designs
b. Using SPSS to analyse and interpret repeated measures ANOVAs
c. Mixed Designs
d. Using SPSS to analyse and interpret Mixed Design ANOVAs
Day 5
a. Hierarchical (Nested) Designs
b. Course recap
c. Consultation session
This course will take place in a computer lab or in a classroom using your own laptop. You will be notified in advance.
If you are asked to bring a laptop you will need SPSS (standard pack) installed. If you do not have SPSS, see the link below in the FAQ to purchase a copy. Otherwise we will provide a link to a trial version. Please note the trail version is only valid for 2 weeks & cannot be installed on the same laptop twice. Please do not activate your trial version until just before te start of the course.
You will be provided with data sets to work on during the sessions, however you are also encouraged to bring along a data set and/or research problem of your own.
Participants should have an understanding of elementary statistics equivalent to the syllabus of ‘Fundamentals of Statistics’.
The instructor's bound, book length course notes will serve as the course texts.
Q: Where can I obtain a copy of SPSS?
A: Hearne software (https://www.hearne.software/Software/SPSS-Grad-Packs-for-Students-by-IBM...) is a trusted website for purchasing student versions of SPSS. People who purchase from this website also receive 24x7 tech support for help with installing SPSS on their own devices
Q: What version of SPSS will I need?
A: You should purchase a student license of SPSS, which comes in three types:
• Statistics premium
• Statistics standard
• Statistics base
As a minimum, you will require the statistics standard version to complete the activities in this course