pt. 1. Graphics: looking at data. A single variable: shape and distribution -- Two variables: establishing relationships -- Time as a variable: time-series analysis -- More than two variables: graphical multivariate analysis -- Intermezzo: a data analysis session -- Analytics: modeling data. Guesstimation and the back of the envelope -- Models from scaling arguments -- Arguments from probability models -- What you really need to know about classical statistics -- Intermezzo: mythbusting -- bigfoot, least squares, and all that -- Computation: mining data. Simulations -- Finding clusters -- Seeing the forest fro the trees: finding important attributes -- Intermezzo: when more is different -- Applications: using data. Reporting, business intelligence, and dashboards -- Financial calculations and modeling -- Predictive analytics -- Epilogue: facts are not reality
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Provides information on the techniques of data analysis using a variety of open source tools