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    Neil R. Smalheiser.
    Reproducibility and robustness -- Choosing a research problem -- Basics of data and data distribution -- Experimental design: measures, validity, sampling, bias, randomization, power -- Experimental design: design strategies and controls -- Power estimation -- The data cleansing and analysis pipeline -- Topics to consider when analyzing data -- Null hypothesis statistical testing and the t-Test -- The "new statistics" and Bayesian inference -- ANOVA -- Non parametric tests -- Correlation and other concepts you should know -- How to record and report your experiments -- Data sharing and reuse -- The revolution in scientific publishing.
    Digital Access  ScienceDirect 2017