Homogeneity of Variance Show
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. This entry focuses on homogeneity of variance as it relates to t tests and ANOVAs. Homogeneity within PopulationsWithin research, it is assumed that populations under observation (e.g., the population of female college students, the population of stay-at-home fathers, or the population of older adults living with type 2 diabetes) will be relatively similar ... locked icon Sign in to access this contentSign in Get a 30 day FREE TRIAL
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commonly used in statistics and econometrics to establish that the values of two outcomes or variables are different from one another. The common assumptions made when doing a t-test include those regarding the scale of measurement, random sampling, normality of data distribution, adequacy of sample size, and equality of variance in standard deviation. The T-TestThe t-test was developed by a chemist working for the Guinness brewing company as a simple way to measure the consistent quality of stout. It was further developed and adapted, and now refers to any test of a statistical hypothesis in which the statistic being tested for is expected to correspond to a t-distribution if the null hypothesis is supported. A t-test is an analysis of two population means through the use of statistical examination; a t-test with two samples is commonly used with small sample sizes, testing the difference between the samples when the variances of two normal distributions are not known. T-distribution is basically any continuous probability distribution that arises from an estimation of the mean of a normally distributed population using a small sample size and an unknown standard deviation for the population. The null hypothesis is the default assumption that no relationship exists between two different measured phenomena. T-Test Assumptions
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What is the assumption that the amount of variability in each of the two groups for a t1. The variability of scores in one group must be equal to the variability of scores in the other group. This assumption is called homogeneity of variances.
What is the term for the measure of the magnitude of the difference between two groups?What Is Effect Size? In medical education research studies that compare different educational interventions, effect size is the magnitude of the difference between groups. The absolute effect size is the difference between the average, or mean, outcomes in two different intervention groups.
Which of the following is a major assumption of the tThe homogeneity-of-variance assumption is an assumption underlying the t-test that states that the amount of variability in both groups is equal.
Which of the following assumptions are required if an independent tAnswer and Explanation: An important assumption for conducting the independent-samples t-test is the homogeneity of variances. This means the variances of both groups should be approximately equal. Hence, the correct answer is option (c) Homogeneity of variance.
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