Chi-Square Test and Its Application
In survey research, mainly two types of hypothesis are tested. One may test goodness of fit for a single attribute or may like to test the significance of association between any two attributes. To test an equal occurrence hypothesis, it is required to ta
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Chi-Square Test and Its Application
Learning Objectives After completing this chapter you should be able to do the following: • • • • •
Know the use of chi-square in analyzing nonparametric data. Understand the application of chi-square in different research situations. Know the advantages of crosstabs analysis. Learn to construct the hypothesis in applying chi-square test. Explain the situations in which different statistics like contingency coefficient, lambda coefficient, phi coefficient, gamma, Cramer’s V, and Kendall tau, for measuring an association between two attributes, can be used. • Learn the procedure of data feeding in preparing the data file for analysis using SPSS. • Describe the procedure of testing an equal occurrence hypothesis and testing the significance of an association in different applications by using SPSS. • Interpret the output of chi-square analysis generated in SPSS.
Introduction In survey research, mainly two types of hypothesis are tested. One may test goodness of fit for a single attribute or may like to test the significance of association between any two attributes. To test an equal occurrence hypothesis, it is required to tabulate the observed frequency for each variable. The chi-square statistic in “nonparametric” section of SPSS may be used to test the hypothesis of equal occurrence. The scores need to be arranged in contingency table for studying an association between any two attributes. A contingency table is the arrangement of frequency in rows and column. The process of creating a contingency table from the observed frequency is known as crosstab. The cross tabulation procedure provides tabulation of two variables in two-way table. A frequency distribution provides the distribution of one variable, whereas a contingency table describes the distribution of two or more variables simultaneously (Table 3.1). J.P. Verma, Data Analysis in Management with SPSS Software, DOI 10.1007/978-81-322-0786-3_3, # Springer India 2013
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3 Chi-Square Test and Its Application
Table 3.1 Preferences of male and female towards different incentives
Incentives Gender
Male Female
Gift check (%)
Cash (%)
Gift article (%)
30 10
45 30
25 60
The following is an example of a 2 3 contingency table. The first variable “gender” has two options, male and female, whereas the second variable “incentives” has three options, gift check, cash, and gift article. Each cell gives the number of individuals who share the combination of traits. The chi-square can be computed by using the Crosstabs option in “Descriptive Statistics” section of SPSS command. Besides chi-square, the Crosstabs option in SPSS provides the output showing magnitude of association along with summary statistics including percentage of frequency and expected frequency in each cell. Two-way tabulation in Crosstabs can be used to establish an interdependent relationship between two tables of values but does not identify a causal relation between the values. Cross tabulation technique can be used to analyze the results of a s
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