Chi squared tests and phi/Cramer’s V are covered in most statistics books, but the bias against categorical data in these sources means there are very few that discuss adjusted standardized residuals (also sometimes referred to as standardized Pearson residuals).

Agresti, A., Franklin, C.A. and Klingenberg, B. (2017) Statistics: The Art and Science of Learning from Data, 4th edn. London: Pearson.
This is one of the few books that discusses the use of standardized residuals for testing the relationship between categorical variables. See chapter 11 (‘Analyzing the association between categorical variables’), especially section 11.4 (‘Using residuals to reveal the pattern of associa­tion’) for a discussion of residuals.

Marchant-Shapiro, T. (2015) Statistics for Political Analysis: Understanding the Numbers. London: Sage/CQ Press.
This book includes some basic instructions for using SPSS to conduct data analysis, and the examples are from political science. See chapter 9 (‘Chi-square and Cramer’s V: What do you expect?’) for chi squared and phi/Cramer’s V. See chapter 11 (‘Multivariate relationships: Taking control’), particularly the section ‘Three-way contingency tables’, for a discussion of crosstabs with more than two variables.

Pallant, J. (2016) SPSS Survival Manual. Maidenhead: Open University Press/McGraw-Hill Education.
This book provides a functional overview of how to produce statistics in SPSS. See chapter 16 (‘Non-parametric statistics’) for a guide to produce chi squared and phi/Cramer’s V.