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... > contexts > population characteristics > health > public health > epidemiology > statistics and research methods > analysis of covariance > homogeneity of variance
... > social science subjects > health and social care > medical science > medicine > clinical medicine > medical decision making > biostatistics and clinical epidemiology > analysis of covariance > homogeneity of variance
... > other subjects > natural sciences > life sciences > medical science > medicine > clinical medicine > medical decision making > biostatistics and clinical epidemiology > analysis of covariance > homogeneity of variance
... > social science subjects > education > educational systems > curriculum > curriculum studies > inquiry and research > quantitative research > quantitative data analysis > analysis of covariance > homogeneity of variance
... > social science subjects > social research > research methods and evaluation > quantitative research > quantitative data analysis > analysis of covariance > homogeneity of variance

Preferred term

homogeneity of variance  

Definition

  • Homogeneity of variance is an assumption underlying both t tests and F tests (analyses of variance, ANOVAs) in which the population variances (i.e., the distribution, or “spread,” of scores around the mean) of two or more samples are considered equal. In correlations and regressions, the term “homogeneity of variance in arrays,” also called “homoskedasticity,” refers to the assumption that, within the population, the variance of Y for each value of X is constant. [Source: Encyclopedia of Research Design; Homogeneity of Variance]

Broader concept

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URI

http://data.loterre.fr/ark:/67375/N9J-MLXZQ22L-T

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