# Survey research and design in psychology/Tutorials/Correlation/Types of correlations - Exercises/Extra exercises

## Nominal by nominal

### Is there an association between favourite season and favourite sense?

Is there an association between favourite season (a8) and favourite sense (a13)?

1. Data file: qfsall_2.sav
2. Univariate frequencies and bar charts.
3. Recode favourite sense (a8) into a8r, changing the mis-entered data (0) and other (6) to system missing - add labels - check frequencies and bar chart.
4. Try out a "stacked area graph". (Graph - Area - Stacked)
5. Crosstabs (using as suggested in Q2-3)
6. χ2 (1, 188) = 8.07, p = .005; Cramer's V = .23 (small-moderate effect and significant)
7. Interpretation: There is a different profile of favourite senses, depending on favourite season (e.g., most 50% of Summer and Spring people are Visual people. Winter people, in contrast, tend to prefer Taste and Smell).

### Is there an association between type of household and whether or not the household has chickens?

1. The datafile (chickens.sav) contains (hypothetical) data for two categorical variables: resid (urban/rural) and chickens (yes/no).
2. Univariate frequencies and bar charts.
3. χ2 (1, 90) = 18.34, p < .001; Φ = -.45 (moderate effect and significant)
4. Interpretation: Rural households are twice as likely to own chickens compared to urban households.

## Dichotomous by interval/ratio

### What is the relationship between Belief in God and number of Countries visited?

What is the relationship between Belief in God (recoded to dichotomous - i.e., b4r) and number of Countries (b8) visited?

1. Data file: qfsall_2.sav
2. Scatterplot - chart options - change to point bins and add line of best fit ("add fit line to total")
3. There may be some outliers who believe in God and who have visited a lot of countries (e.g., over 20) who are "creating" the small, non-significant correlation.
4. Correlation - bivariate
5. rpb = -.10, p = .29, N = 127 (small, negative and non-significant, i.e., people who believe in God (coded 0) have travelled to more countries than people who don't believe in God (coded 1). Note, however, this could be due to some outliers and/or a third variable, such as age.