[amp_mcq option1=”Visualizing data” option2=”Feature selection” option3=”Assessing the goodness of fit of a sample distribution to a theoretical distribution” option4=”Clustering” correct=”option3″]<\/p>\n
The correct answer is C. Assessing the goodness of fit of a sample distribution to a theoretical distribution.<\/p>\n
The Kolmogorov-Smirnov test is a nonparametric test that is used to compare two continuous distributions. It is used to determine whether two samples come from the same population or not. The test is based on the maximum absolute difference between the cumulative distribution functions of the two samples.<\/p>\n
The Kolmogorov-Smirnov test is a powerful test and can be used to compare two samples even if the distributions are not normal. However, it is important to note that the test is not robust to outliers.<\/p>\n
Option A is incorrect because the Kolmogorov-Smirnov test is not used to visualize data. Option B is incorrect because the Kolmogorov-Smirnov test is not used for feature selection. Option D is incorrect because the Kolmogorov-Smirnov test is not used for clustering.<\/p>\n","protected":false},"excerpt":{"rendered":"
[amp_mcq option1=”Visualizing data” option2=”Feature selection” option3=”Assessing the goodness of fit of a sample distribution to a theoretical distribution” option4=”Clustering” correct=”option3″]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[738],"tags":[],"class_list":["post-46609","post","type-post","status-publish","format-standard","hentry","category-data-science-miscellaneous","no-featured-image-padding"],"yoast_head":"\n