SSCI2020 Workshop 7: Exploring the 2009 AuSSA Data

This week workshop will not introduce new data analysis skills. Instead, you will use data analysis skills you have learned so far and analyse a new dataset, the 2009 Australian Survey of Social Attitudes (2009 AuSSA). Since this workshop is the first workshop after the recess period, this workshop will be an excellent opportunity to refresh what you have learned so far in the workshops. You may need to go back to the previous workshop instructions, but this will give you a chance to review important SPSS techniques that will be used for the final data analysis report.

In this workshop, you are required to complete four tasks. The four tasks will make you ready to answer the Workshop 7 Participation questions.

2009 AuSSA

Workshop 7 will use the 2009 Australian Survey of Social Attitudes (2009 AuSSA). The main topic of the 2009 AuSSA is “social inequality”. The dataset is extracted from the 2009 International Social Survey Program (ISSP) data but includes only Australian respondents. The 2009 AuSSA is one of three datasets which you can use for your final survey report. If you want to know more about the 2009 AuSSA, see https://dataverse.ada.edu.au/dataset.xhtml?persistentId=doi:10.4225/87/IH68HQ.

Go to the course iLearn page and find The 2009 AuSSA SPSS Data File under the section of Datasets. Download this file. The downloaded data file should be aussa2009.sav. If you completed Preparation for the Workshops, this data file is already in your SSCI2020 folder at AppStream. Also, download and look at A Simple Codebook of the 2009 AuSSA and A Detailed Codebook of the 2009 AuSSA which all provide useful information on variables and their values in the dataset.

Task 1: Frequency table

In an open society, top positions are allowed for anyone who aims to achieve them, and thus an individual’s effort rather than family background determines accomplishments in their life. Let’s examine how Australians see opportunities to get ahead in society using two variables: opwlth and ophrdwrk. The first variable, opwlth, measures how respondents assess the extent to which it is important to come from a wealthy family in getting ahead in society. The next variable, ophrdwrk, measures how respondents assess the extent to which it is important to work hard in getting ahead in society. Five response options are provided(See A Simple Codebook of the 2009 AuSSA or A Detailed Codebook of the 2009 AuSSA):

  • 1: Essential
  • 2: Very important
  • 3: Fairly important
  • 4: Not very important
  • 5: Not important at all

To explore these two variables, Make frequency tables of these two variables(opwlth and ophrdwrk) (Tip: If you are not sure how to make a frequency tabe, see Making a frequency table.).

Task 2: Recoding a variable

MAKE a new class variable (newclass) by recoding class following the recoding scheme in <Table 1> in the below (Tip: If you are not sure how to recode variables, see Recoding variables.). Then, make a frequency table of newclass.

Table 1: Recoding scheme for new class variable
Old variable(class)
New variable(newclass)
Values Labels Values Labels
1 Lower 1 Lower
2 Working 1 Lower
3 Lower middle 1 Lower
4 Middle 2 Middle
5 Upper middle 3 Upper
6 Upper 3 Upper

Task 3: Descriptive statistics by groups

Suppose that you want to compare the average age between classes. Compute the average age for lower, middle, and upper class, respectively. Use age and newclass that you just made for this task. (Tip: If you are not sure how to compute descriptive statistics by groups, see Comparing descriptive statistics between groups using Explore.).

Task 4: Selecting cases

Suppose that you want to analyse only respondents residing in NSW and make a frequency table of opwlth (which you used in Task 1). Thus, you need to 1) select respondents residing in NSW and then 2) make a frequency table of opwlth.

To select respondents residing in NSW, use region variable. region has the following 8 values (See A Simple Codebook of the 2009 AuSSA or A Detailed Codebook of the 2009 AuSSA):

  • 1: New South Wales
  • 2: Victoria
  • 3: Queensland
  • 4: South Australia
  • 5: Western Australia
  • 6: Tasmania
  • 7: Australian Capital Territory
  • 8: Northern Territory.

If you are not sure how to select cases, see Selecting cases. After making a frequency table of opwlth, don’t forget to deselect cases before you save the dataset.Otherwise, your future analysis on this dataset will analyse only respondents in NSW.

Workshop Activity 7: Exploring the 2009 AuSSA Data

  1. Based on the frequency tables of Task 1, which statement is NOT correct?
     (1) 2.8% of respondents see wealthy family background essential.
     (2) The median response of opwlth variable is “Fairly important”
     (3) A higher percent of respondents see wealthy family background important or essential.
     (4) 44.2% of respondents see hard work essential.
     (5) A higher percent of people see hard work important or essential.


  1. Based on the frequency tables of Task 2, report the percent of middle class. Please report just a number (e.g., If you get 15.6%, report 15.6). You can find it in Valid percent. Do not include % in the answer.


  1. Based on the descriptive statistics of Task 3, Which class has the highest average age?


  1. Based on the frequency table of Task 4, what is the percent of respondents who see wealthy family background “fairly important”? Please report just a number (e.g., If you get 15.6%, report 15.6). You can find it in Valid percent. Do not include % in the answer.


Last updated on 29 September, 2021 by Dr Hang Young Lee(hangyoung.lee@mq.edu.au)