Understanding statistics

	Mobile Survey Participant Information About Us Careers Help Contact Us
	Australian Bureau of Statistics


Module 3. Interpreting Data


	Lesson 1.	Introduction and review
		1.1	Review
		1.2	Module objectives
		1.3	Case study

	Lesson 2.	Using data to support an argument

	Lesson 3.	Questioning the data
		3.1	Was the variable well defined?
		3.2	How were the data produced?

	Lesson 4.	Using summaries of data to support an argument
		4.1	Estimating a population parameter from a sample statistic and estimating the size of a sample.
		4.2	Using null and alternative hypotheses
		4.3	What is the statistical meaning of 'significant'?
		4.4	Does statistically significant mean practically significant?
		4.5	How important is hypothesis testing in the production of data

	Lesson 5.	Association between two variables
		5.1	Revision and introduction
		5.2	What types of relationship might exist between two quantitative variables?
			5.2.1		Deterministic relationship
			5.2.2		Statistical relationship
		5.3	Scatter plots
			5.3.1	Example of a scatterplot
			5.3.2	Conventions for scatterplots
			5.3.3	How can you interpret a scatter plot?
			5.3.4	The correlation coefficient, r
			5.3.5	The line of best fit (regression line)
			5.3.6	Using the regression line to forecast
			5.3.7	What happened to frequency?
			5.3.8	Using a calculator for bivariate data
		5.4	What about qualitative/categorical variables?

	Lesson 6.	What about causation in observational studies? Beware the confounding variable!
		6.1	Confusion of scales
		6.2	Are confounding variables only found with categorical data?

	Lesson 7.	How are studies constructed and how is causation established in observational studies?
		7.1	Case Study: Vaginal cancer and synthetic oestrogen, DES
		7.2	Case Study: Lung cancer and smoking

	Lesson 8.	What relationships are possible between variables?

	Lesson 9.	What about time? Time series plots

	Lesson 10.	What are the steps to statistical literacy?
	End Notes Source Materials

This page last updated 30 November 2009

Australian Bureau of Statistics

Menu