Argyrous, G. (2011) Statistics for Research with a Guide to SPSS, 3rd edn. London: SAGE.
Chapter 5 covers using crosstabulations to investigate the relationships between variables. Chapter 6 focuses mainly on the coefficient lambda for nominal variables and Chapter 7 on gamma for ordered category variables. Note that Argyrous says this statistic is for ‘ranked’ data, but not ranked in the sense used in Kent (2015). Correlation and regression are considered in Chapter 12.
De Vaus, D. (2002) Analyzing Social Science Data: 50 Key Problems and Data Analysis. London: SAGE.
Part 6 is on how to analyse two variables. Problems 32, 35 and 37 are particularly useful; 39 and 40 can be skipped.
Diamantopoulos, A. and Schlegelmilch, B. (1997) Taking the Fear Out of Data Analysis. London: Dryden Press. Republished by Cengage Learning, 2000.
Chapter 13 is brief, but it explains Cramer’s V, Spearman’s rho and Pearson’s r.
Yang, K. (2010) Making Sense of Statistical Methods in Social Research. London: SAGE.
Chapter 6 on studying the relationship between two variables is well worth reading. Be warned, however, that for two nominal variables, Yang focuses in the chi-square test for evidence of the existence of a relationship (but presuming a random sample), and for the strength of the relationship recommends the odds ratio.