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Chi-square Test and Exact Binomial Method for One Proportion


Output 1. Proportion Plot



Output 2. Test Results


1. Normal Theory Method with Yates' Continuity Correction, when np0(1-p0) >= 5


2. Exact Binomial Method, when np0(1-p0) < 5


Explanations
  • P Value < 0.05, then the population proportion/rate IS significantly different from the specified proportion/rate. (Accept the alternative hypothesis)
  • P Value >= 0.05, then the population proportion/rate IS NOT significantly different from the specified proportion/rate. (Accept the null hypothesis)

Chi-square Test for Two Independent Proportions


Output 1. Data Preview


Data Table

Percentage Plot of

1. Case

2. Control


Output 2. Test Results


Explanations
  • P Value < 0.05, then the population proportion/rate are significantly different in two groups. (Accept alternative hypothesis)
  • P Value >= 0.05, then the population proportion/rate are NOT significantly different in two groups. (Accept null hypothesis)

Chi-square Test for More than Two Independent Proportions


Output 1. Data Preview



Data Table


Output 2. Test Results


Explanations
  • P Value < 0.05, then the population proportion/rate are significantly different. (Accept the alternative hypothesis)
  • P Value >= 0.05, then the population proportion/rate are NOT significantly different. (Accept the null hypothesis)

Chi-square Test for Trend in Multiple Independent Samples


Output 1. Contingency Table



Data Table

Cell-Column %


Output 2. Test Results


Explanations
  • P Value < 0.05, then Case-Control (Row) is significantly associated with grouped Factors (Column) (Accept the alternative hypothesis)
  • P Value >= 0.05, then Case-Control (Row) is not associated with grouped Factors (Column). (Accept the null hypothesis)