Similarities between Nomogram and Yates's correction for continuity
Nomogram and Yates's correction for continuity have 2 things in common (in Unionpedia): Pearson's chi-squared test, Type I and type II errors.
Pearson's chi-squared test
Pearson's chi-squared test (χ) is a statistical test applied to sets of categorical data to evaluate how likely it is that any observed difference between the sets arose by chance.
Nomogram and Pearson's chi-squared test · Pearson's chi-squared test and Yates's correction for continuity ·
Type I and type II errors
In statistical hypothesis testing, a type I error is the rejection of a true null hypothesis (also known as a "false positive" finding), while a type II error is failing to reject a false null hypothesis (also known as a "false negative" finding).
Nomogram and Type I and type II errors · Type I and type II errors and Yates's correction for continuity ·
The list above answers the following questions
- What Nomogram and Yates's correction for continuity have in common
- What are the similarities between Nomogram and Yates's correction for continuity
Nomogram and Yates's correction for continuity Comparison
Nomogram has 40 relations, while Yates's correction for continuity has 15. As they have in common 2, the Jaccard index is 3.64% = 2 / (40 + 15).
References
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