有关于卡方检验的结果?谁能帮我分析一下?Chi-Square TestsValue df Asymp.Sig.(2-sided)Pearson Chi-Square 29.990(a) 5 .000Likelihood Ratio 39.871 5 .000N of Valid Cases 256 a 1 cells (8.3%) have expected count less than 5.The minimum exp
来源:学生作业帮助网 编辑:作业帮 时间:2024/11/09 00:32:07
有关于卡方检验的结果?谁能帮我分析一下?Chi-Square TestsValue df Asymp.Sig.(2-sided)Pearson Chi-Square 29.990(a) 5 .000Likelihood Ratio 39.871 5 .000N of Valid Cases 256 a 1 cells (8.3%) have expected count less than 5.The minimum exp
有关于卡方检验的结果?谁能帮我分析一下?
Chi-Square Tests
Value df Asymp.Sig.(2-sided)
Pearson Chi-Square 29.990(a) 5 .000
Likelihood Ratio 39.871 5 .000
N of Valid Cases 256
a 1 cells (8.3%) have expected count less than 5.The minimum expected count is 4.21.
卡方检验结果如上,本人统计基础差 没有办法解释上述检验结果
Value df Asymp.Sig.(2-sided)
Pearson Chi-Square 29.990(a) 5 .000
Likelihood Ratio 39.871 5 .000
N of Valid Cases 256
a 1 cells (8.3%) have expected count less than 5.The minimum expected count is 4.21
这个表格感觉比较清楚了
有关于卡方检验的结果?谁能帮我分析一下?Chi-Square TestsValue df Asymp.Sig.(2-sided)Pearson Chi-Square 29.990(a) 5 .000Likelihood Ratio 39.871 5 .000N of Valid Cases 256 a 1 cells (8.3%) have expected count less than 5.The minimum exp
先进行单因素分析,可选用卡方检验,因为你所说的自变量均为分类资料,进而筛选对因变量有影响的自变量;然后将入选的自变量进行多因素分析,如Logistic回归分析,可选用逐步回归,进而判定自变量对因变量的影响大小.(此处因变量应为观点的分布,卡方检验时将性别、年龄及工作同时调入列变量,SPSS会给出三个列联表,根据P值找出适宜的自变量;因为因变量为分类资料,故一般的线性回归是不可以的,而Logistic回归对这类资料就比较适用了,可以找出对因变量贡献最大的自变量).