Title: Self test - Associations between 2 variables
Course: UGQuants (SSPS) > Section: Associations Between 2 Variables

Exercise 1: IV and DV

For each of the following pairs of variables, indicate which is most likely to be the independent (IV) and which the dependent variable (DV) in any association between the variables:

  1. Respondent’s highest educational qualification and whether or not s/he has taken part in lawful public demonstration last 12 months
  2. Respondent’s highest educational qualification and father’s occupation when respondent was 14 years old
  3. Respondent’s age and respondent’s fear of crime
  4. Respondent’s sex and respondent’s personal income
  5. Respondent’s attitudes to women working less when they have family and his/her religious denomination
  6. Respondent’s housing tenure and his/her children’s level of attainment at school

Exercise 1: Answer

For each of the following pairs of variables, indicate which is most likely to be the independent (IV) and which the dependent variable (DV) in any association between the variables:

  1. Respondent’s highest educational qualification (IV) and whether or not s/he has taken part in lawful public demonstration last 12 months (DV)
  2. Respondent’s highest educational qualification (DV) and father’s occupation when respondent was 14 years old (IV)
  3. Respondent’s age (IV) and respondent’s fear of crime (DV)
  4. Respondent’s sex (IV) and respondent’s personal income (DV)
  5. Respondent’s attitudes to women working less when they have family (DV) and his/her religious denomination (IV)
  6. Respondent’s housing tenure (DV) and his/her children’s level of attainment at school (IV)

Try to identify what came first: e.g. the father's occupation when the respondent was 14 years old likely came before the person finished school. We can hypothesise that a well earning father may be better able to send his child off for advanced schooling than someone with little income. Contrarily, it would be hard to imagine that your fear of crime makes you older - perhaps in appearance, if it is a deeply rooted fear, but certainly not in measurable time.

Exercise 2: Contingency tables

Using data from the European Social Survey round 5 practice dataset, create a contingency table for gender (‘gndr’) and subjective health (‘health’). Answer the following questions:

  1. Are men or women more likely to believe that their health is good?
  2. What percentage of women describe their health as very good?
  3. What percentage of all cases in the table describe their health as bad or very bad?

Exercise 2: Answer

Using the European Social Survey round 5 practice dataset, create a contingency table for gender (‘gndr’) and subjective health (‘health’). Answer the following questions:

  1. Are men or women more likely to believe that their health is good?
  2. What percentage of women describe their health as very good?
  3. What percentage of all cases in the table describe their health as bad or very bad?

1. Women are slightly (2.2%) more likely to say their health is very good, but equal shares of men and women say their health is good.
2. 29.5%.
3. 6.0% + 1.5% = 7.5%.

Exercise 3: Contingency tables + recoding

Using the European Social Survey round 5 practice dataset, create a contingency table for highest educational qualification in the UK ('edulvlb' ) and whether or not the respondent has contacted a politician or government official in the last 12 months (‘contplt’). Answer the following questions:

  1. What percentage of all cases in the table have contacted a politician or government official in the last 12 months?
  2. Are people who have degrees or other higher education qualifications more or less likely to have contacted a politician or government official in the last 12 months?
  3. What percentage of people with no qualifications have contacted a politician or government official in the last 12 months?

Exercise 3 - Answer

What percentage of all cases in the table have contacted a politician or government official in the last 12 months?

Are people who have degrees or other higher education qualifications more or less likely to have contacted a politician or government official in the last 12 months than people with no such qualification?

What percentage of people with no qualifications have contacted a politician or government official in the last 12 months?

As the name of the exercise suggests, you are best advised to recode 'edulvlb' into fewer categories to be able to make sense of the table you produce. The first hurdle when recoding 'edulvlb' is knowing what all the various response categories for level of education actually mean - you might need to research some of them. Here, we decided that all categories with the code 610 or higher are (university) degrees. Our SPSS syntax is as follows:

RECODE edulvlb (0=0) (MISSING=SYSMIS) (610 thru Highest=2) (1 thru 600=1) INTO edulvlb_3cat.
EXECUTE. (notice that we created a new variable)

Now we can produce our table. Because we assume that level of education might have an influence on whether someone contacts politicians, we put it (the IV) into the columns and contacting politicians (DV) in the rows. We have added column percentages. This is a table produced in SPSS, but any other software should yield the same results:

First, we are interested in the percentage of all cases in the table who have contacted a politician in the last twelve months before the interview. This we find in the very last column, which shows us the total count, independent of the level of education. The answer is 15%.

Secondly, we want to compare several groups. We can see that amongst people with no degree, 13% contacted a politician within the last 12 months; amongst those with a degree, 22.4% did so. It looks like people with a university degree are more likely to contact politicians.

Last but not least, we want to see what this is like for people with no school education at all. Our column percentages suggest they just don't contact politicians. But stop! -Look at the absolute counts: we actually don't have enough people with no education in our sample to be able to make any general statements about them - there is only one.

Exercise 4: Comparing means

Use the compare means procedure to examine the associations between the following pairs of variables in the European Social Survey round 5 practice dataset, answering the question for each one:

  1. Years completed in full-time education (‘eduyrs’) and whether respondent has boycotted any products in the last year (‘bctprd’). Are people who have spent more years in full-time education more or less likely to have boycotted products?
  2. Age of respondent (‘agea’) and his/her agreement or disagreement with the statement ‘Gay men and lesbians should be free to live their own life as they wish’ (‘freehms’). Are older or younger people more likely to be tolerant towards gay and lesbian people?

Exercise 4: Answer

Use the compare means procedure to examine the associations between the following pairs of variables in the European Social Survey round 5 practice dataset, answering the question for each one:

  1. Years completed in full-time education (‘eduyrs’) and whether respondent has boycotted any products in the last year (‘bctprd’). Are people who have spent more years in full-time education more or less likely to have boycotted products?
  2. Age of respondent (‘agea’) and his/her agreement or disagreement with the statement ‘Gay men and lesbians should be free to live their own life as they wish’ (‘freehms’). Are older or younger people more likely to be tolerant towards gay and lesbian people?

1. People who have boycotted products in the last 12 months have spent an average of 14.24 years in education. The other group only spent 12.92 years in education.
2. Tentatively, we could say older people are more likely to be against gay and lesbian couples. However, there is no clear linear trend: those strongly agreeing with the statement ‘Gay men and lesbians should be free to live their own life as they wish’ are on average the youngest with  44.58 years, but those who agree [though not strongly] are older with an average of 51.11 years than those who neither agree nor disagree (45.18 years). The strongly disagreeing group also does not have the highest negative age. We might want to investigate this further with data from other sources (or in our case: with the full ESS5 dataset, which has four times more respondents).