Homoskedastic

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Homoskedastic

Describing a sequence of variables where each variable has the same or a very similar variance. Homoskedasticity is often assumed in statistics but is not always true. See also: Heteroskedastic.
References in periodicals archive ?
In practical situations, where the response variable is the count of the number of thrips over time, the homoscedasticity assumption may not be reasonable (Mazucheli et al., 2011).
Homoscedasticity was established by visual inspection of a plot of studentized residuals versus unstandardized predicted values.
Normality and homoscedasticity were individually analysed for each variable, transforming the variable when necessary.
Survival results for field seedlings were subjected to normality tests (p-value = 0.5126) and homoscedasticity of variance (F calculated = 0.95 and F tabulated = 4.74) test, the data was observed to fulfill the assumptions from analysis of variance (ANOVA) (Table 1).
To examine whether or not the relationship between the dependent variable (cyberbullying) and the predictive variables (demographics and the use of information and communication technologies) was linear and whether or not the scores displayed normal distribution, we then ran an SPSS scatterplot and checked the plots departing from linearity and homoscedasticity. Our examination of the histogram and plot of the standardized residuals in the regression analysis revealed that skewness and kurtosis values were within acceptable boundaries and that homoscedasticity was achieved.
The inspection of assumptions of multicollinearity, homoscedasticity, linearity of the model, and the independence and normal distribution of the errors indicate that regression results could be generalizable to the population.
Efficiency of all carrier materials was calculated after measuring agro-economic traits and the best carrier material was evaluated according to Shazia et al., (2015).Moreover, correlations among carrier materials, inducers, DS and agroeconomic traits were also determined by calculating homoscedasticity.
Data were tested using tests of demographic characteristics, multivariate assumptions (normality, linearity, and homoscedasticity), reliability, descriptive (mean, standard deviation, skewness, and kurtosis), correlation and multiple regression.
Using Pearson product-moment correlation, preliminary analyses were performed to ensure no violation of the assumptions of normality, linearity and homoscedasticity. Table 2 shows value of "r" depicting strength of relationship among variables along with "p" value which depicts level of significance.
The ANOVA also has the assumption that the groups being compared have similar variances or spreads in their scores (this is called homoscedasticity).
Data of percent area occupied by weeds were analyzed for data homoscedasticity and normality, to verify assumptions for parametric analysis.
Dispersions of all [[epsilon].sub.i] are equal (homoscedasticity assumption).