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pre-assumptions_of_regression_analysis

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pre-assumptions_of_regression_analysis [2016/05/02 08:31] – [pre-asumptions in regression test] hkimscilpre-assumptions_of_regression_analysis [2016/05/09 09:23] hkimscil
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 ====== pre-asumptions in regression test ====== ====== pre-asumptions in regression test ======
   * [[Linearity]] - the relationships between the predictors and the outcome variable should be linear   * [[Linearity]] - the relationships between the predictors and the outcome variable should be linear
-  * [Normality]] - the errors should be normally distributed - technically normality is necessary only for the t-tests to be valid, estimation of the coefficients only requires that the errors be identically and independently distributed+  * [[:Normality]] - the errors should be normally distributed - technically normality is necessary only for the t-tests to be valid, estimation of the coefficients only requires that the errors be identically and independently distributed
   * [[:Homoscedasticity|Homogeneity]] of variance (or [[Homoscedasticity]]) - the error variance should be constant   * [[:Homoscedasticity|Homogeneity]] of variance (or [[Homoscedasticity]]) - the error variance should be constant
   * Independence - the errors associated with one observation are not correlated with the errors of any other observation   * Independence - the errors associated with one observation are not correlated with the errors of any other observation
pre-assumptions_of_regression_analysis.txt · Last modified: 2016/05/11 08:37 by hkimscil

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