Chi-square Test
Categorical-data hypothesis testing in pharmacology research
Past RGUHS + DNB + MPMSU + MUHS · 11
RGUHSJun '24
DNBMay '24
RGUHSMay '22
RGUHSNov '21
MUHSSummer '19
MPMSUMay '18
RGUHSNov '17
MPMSU2010
RGUHSOct '08
RGUHSSep '07
MPMSU2002
Introduction
- Definition — Chi-square (χ2) is a family of non-parametric inferential tests comparing observed (O) and expected (E) frequencies in categorical data against the χ2 sampling distribution.
- Test family — Four named variants — Pearson goodness-of-fit, Pearson independence, χ2 of homogeneity, and McNemar (paired) — plus Mantel–Haenszel (stratified), Cochran–Armitage (trend), and the likelihood-ratio G2 statistic.
- Historical anchor — Pearson 1900 introduced χ2 as the first general goodness-of-fit test; Yates 1934 added the continuity correction; Fisher 1934 defined the exact alternative; McNemar 1947 adapted it for paired binary data.
- MD pharmacology relevance — First-line test for categorical outcomes in pharmacology — drug-vs-placebo response rates, ADR incidence, genotype frequencies, and ordered-category survey responses.
- RGUHS / NMC — Recurring 10-mark RGUHS LAQ (6 verbatim recurrences in the past-question corpus + 3 MPMSU); NMC PG competency PG2.5 — apply appropriate biostatistical tests.
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Chi Square Test
PharmaNotes Pro · LAQ
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