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DATA201: Techniques of Data ScienceStephen Marsland[email protected]School of Mathematics and StatisticsVictoria University of WellingtonStephen Marsland(VUW)1
Data ScienceStephen Marsland(VUW)2
Data ScienceStephen Marsland(VUW)3
Data ScienceStephen Marsland(VUW)4
Data ScienceAim to make data usefulDataInformationKnowledgeUnderstandingWisdomStephen Marsland(VUW)5
Data Science[Drew Conway]Stephen Marsland(VUW)6
Data Science[udacity.com]Stephen Marsland(VUW)7
The Data Science ProcessUnderstand the problemSometimes called framing, this is concerned withfinding out where data analysis is needed, what information isavailable, and gaining some idea about the domain. It usuallyconsists of asking questions and verifying the answers.Select dataWhat data would you like to have? What data is available?Is it correct? Is it representative, or biased in some way? Arethere legal or ethical issues to do with it? Is some data youneed missing?Wrangle the data‘Argue’ with the data to get it into a state that it isusable. Could involve removing errors, combining datasets,transforming the numbers in some way. The aim is to have aclean set of numbers for use.Stephen Marsland(VUW)8
The Data Science ProcessExplore the dataBuild some intuition up about the data by making someplots, getting some summary statistics, checking if there areoutliers.Build modelsChoose appropriate methods to model the data, and then fitthem to test data.Analyse the resultsLook at the results. Use your intuition and knowledgeabout it to make sure that the results make sense. Build newmodels or refine the old ones.

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