The principle of paired chi square test is based on chi square test. For each participant, pair the two measurement results and construct a matching table to calculate the chi square statistic. Then, by comparing the significance level of chi square statistics with the number of degrees of freedom, it is determined whether the pairing of the two variables is statistically significant.

    Data description:

    Background description:

    This study used paired chi square tests to evaluate the pairing between two related variables. Paired chi square test is applicable to the comparison of pairedness between two measurements of two variables. For example, paired chi square tests can be used to compare whether there are differences in the behavior of the same group of participants at two time points.

    In this example, due to the p-value being greater than 0.05, we cannot conclude that there is a significant pairing between these two variables in the population. This means that the pairing between these two variables in the sample is not statistically significant and may be due to random factors.

    The analysis results are as follows:

     The chi square test results show that using chi square test (cross analysis) to study the difference relationship between data, it can be seen from the above table that the p-value is 1.0>0.05, the chi square value is 27.64, and the degree of freedom is 80, indicating that there is no significant difference between the data, and the data distribution is relatively uniform.

    statistic χ The value of 2 is 27.640, the degree of freedom is 80, and the p-value is 1.000. Due to the p-value being greater than 0.05, we accept the original assumption that there is no significant pairwise relationship between the two variables in the population.

    Detailed explanation of indicators:

    1.χ 2-value: This value is a statistic of paired chi square analysis. It measures the pairing between two variables. In this example, the paired chi square statistic χ The 2 value is 27.640.

    2.Degrees of Freedom: Degrees of freedom refer to the degree of freedom used for calculating χ The number of independent information with 2 values. In this example, the degree of freedom is 80.

    3.P-value: The p-value of paired chi square test is used to determine whether the pairing between two variables is statistically significant. In this example, the p-value is 1.000.

关注微信公众号发送【示例数据】获取SPSSMAX练习示例数据。