পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| ক্রেমারের ভি× | ফিশারের নির্ভুল পরীক্ষা× | লজিস্টিক রিগ্রেশন× | |
|---|---|---|---|
| ক্ষেত্র≠ | পরিসংখ্যান | পরিসংখ্যান | গবেষণা পরিসংখ্যান |
| পরিবার≠ | Hypothesis test | Hypothesis test | Process / pipeline |
| উদ্ভবের বছর≠ | 1946 | 1922 | 1958 |
| প্রবর্তক≠ | Harald Cramér | R. A. Fisher | David Roxbee Cox |
| ধরন≠ | Nonparametric association measure | Exact test of independence for categorical data | Method |
| মৌলিক উৎস≠ | Cramér, H. (1946). Mathematical Methods of Statistics. Princeton University Press. ISBN: 978-0691080420 | Fisher, R. A. (1922). On the interpretation of chi-squared from contingency tables, and the calculation of P. Journal of the Royal Statistical Society, 85(1), 87–94. DOI ↗ | Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗ |
| অপর নাম≠ | cramers v, cramer v, phi coefficient (r×c), Cramer's V (İlişki Kuvveti) | Fisher-Irwin test, exact test of independence, Fisher'ın Kesin Testi | logit model, binomial logistic regression, LR |
| সম্পর্কিত≠ | 3 | 2 | 3 |
| সারসংক্ষেপ≠ | Cramer's V is a nonparametric effect-size statistic that measures the strength of association between two categorical variables on a scale from 0 to 1. Introduced by the Swedish mathematician Harald Cramér in his 1946 work Mathematical Methods of Statistics, it generalises the phi coefficient to tables of any size, making it the standard companion statistic to the chi-square test. | Fisher's exact test is a nonparametric exact-probability test of independence for small-sample contingency tables, introduced by R. A. Fisher in 1922. Rather than relying on a large-sample approximation, it computes the exact probability of the observed table directly from the hypergeometric distribution. | Logistic regression is a statistical method for modeling the probability of a binary outcome (disease present/absent, success/failure) as a function of continuous and categorical predictors. Developed by David Roxbee Cox (1958), it solves the problem of predicting categorical outcomes by applying a logistic transformation to constrain predictions to the [0,1] probability interval, enabling accurate risk stratification, diagnostic prediction, and causal inference in epidemiology, medicine, and social science. |
| ScholarGateডেটাসেট ↗ |
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