ScholarGate
Assistent

Compara mètodes

Revisa els mètodes seleccionats l'un al costat de l'altre; les files que difereixen es ressalten.

Anàlisi de tabulació creuada×Estadística Descriptiva×
CampEstadísticaEstadística
FamíliaHypothesis testHypothesis test
Any d'origen19001977
Autor originalKarl PearsonJohn W. Tukey
TipusDescriptive and inferential categorical analysisSummary procedure
Font seminalPearson, K. (1900). On the criterion that a given system of deviations from the probable in the case of a correlated system of variables is such that it can be reasonably supposed to have arisen from random sampling. Philosophical Magazine, 50(302), 157–175. DOI ↗Tukey, J.W. (1977). Exploratory Data Analysis. Addison-Wesley. ISBN: 978-0201076165
Àliescrosstab, contingency table analysis, two-way frequency table, bivariate frequency analysissummary statistics, exploratory data summary, Betimsel İstatistik
Relacionats56
ResumCross-tabulation analysis (contingency table analysis) is a foundational descriptive and inferential technique for examining the relationship between two or more categorical variables. It arranges observed frequencies into a table of rows and columns, enabling visual inspection of patterns and formal chi-square testing of independence between the variables.Descriptive statistics is a set of procedures that numerically and visually summarises the essential characteristics of a dataset: central tendency (mean, median, mode), spread (standard deviation, interquartile range), shape (skewness, kurtosis), and frequency distributions. Systematised for applied data analysis by John W. Tukey in his 1977 work on Exploratory Data Analysis, descriptive statistics serves as the indispensable first step before any inferential or modelling procedure.
ScholarGateConjunt de dades
  1. v1
  2. 2 Fonts
  3. PUBLISHED
  1. v1
  2. 1 Fonts
  3. PUBLISHED

Ves a la cerca Baixa les diapositives

ScholarGateCompara mètodes: Cross-tabulation analysis · Descriptive Statistics. Recuperat el 2026-06-17 de https://scholargate.app/ca/compare