Importance of the Research
Discussion
Fox (2011) article “Non-Normally Distributed Errors In Regression Diagnostics” evaluates errors found in non-normal distribution. The researcher considers the robustness of validity estimation of least squares that is maximally efficient in normal distribution but gives rise to mistakes in non-normal distribution. Skewed and multimodal error distributions also provide an examination of the distribution of the residuals about the error of the model in application.
Importance of the Research
The statistical inferences conducted by the researcher is essential to understanding the subject of the problem by showing a graphical representation of the non-normally distributed error. The study considers an independent randomized sample of studentized residuals regarding a unit normal distribution. The population of the study comprise of studentized residuals, and the particular problem being solved by Fox (2011) is the skewed error distribution in non-normally distributed data samples.
Model Equation
The dependent variable in this research is the non-normal distribution error as a function of (X), of which X might be the size of the samples. (E) connotes to the other factors that might potentially skew the results of the variables. The studentized residuals, t(n), represent the factor of X that is an independent variable to Y. Y is the function of non-normal distribution error in studentized residuals.
Research Error
Though there is minimal probability of error in this research, sampling error might still be present. Fox (2011) has taken explicit care to utilize representative population to portray a near-perfect graphical representation of the research problem. Still, a study of this nature cannot be explicit enough to comprise all required sample elements in the study population.
Reference
Fox, J. (2011). Regression diagnostics: An introduction (Vol. 79). SAGE Publications, Incorporated.