ABSTRACT
This chapter focuses on bivariate statistical analysis and shows how to read and construct cross-tables of data and deciding which statistics to use to measure association and correlation. It suggests how to reject or accept a hypothesis using the appropriate statistics to assess bivariate relationships. The chapter focuses on developing skills for accomplishing these objectives through bivariate data analysis and for understanding measures of correlation and association. Constructing frequency tables for variables simultaneously is a good way to start analyzing the variables in hypotheses. Crosstabs are ideally suited to nominal or ordinal measured variables or to interval/ratio data with a very limited number of discrete values. Crosstabs illustrate whether some relationship is occurring with the data. The probability of obtaining a chi-square value by chance for a particular number of cells in a table is determined by the computer program that compares the value to a normal curve table of probabilities.
