We shall now construct a QQ plot for the given dataset to test it against the distribution of N(1, 2). For simplicity, we have taken only 10 observations. However, using R or any other programming language, the interpretation can be extended to any finite nu...
Create a QQ plot of the sample data against a theoretical normal distribution: sm.qqplot(data, line='45') plt.show() 1. 2. Interpretation of QQ Plot In a QQ plot, if the data points fall approximately along a straight line, it suggests that the data follows the distribution being comp...
principled decision. Numerous tests have been proposed in the literature (in particular in order to test normality) and we focus here on the Anderson-Darling test. For an observed sample x1,...,xn the Anderson-Darling (AD) test statistic is given by T(x1,...,xn) = nZ +1 1(Fn(y) ...