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Write description for each chapter of analysis. Whenever necessary, modify the code to match a good analysis and a clear red line through the paper
Overdue by 7 year(s)•Due by July 18, 2019•0/7 issues closed- data manipulation (in R or in Python) - visualization using a grammar of graphics - reports with RMarkdown that are consistent (including sections, numbered floating elements, maybe citations and formulars) - clean summary tables - comparison of groups, in order to estimate a treatment effect (inference, p-values, ...) - how out of sample (prediction) error can be decomposed in to bias, variance and non-reducible error. How this decomposition can guide the choice of a complexity parameter (avoid overfitting), or can help improve the quality of the prediction.
Overdue by 7 year(s)•Due by July 11, 2019•4/8 issues closed