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1. 1. Fisher's Randomization Test versus Neyman's Average Treatment Test

   Kandidat-uppsats, Uppsala universitet/Statistiska institutionen

   Författare :Kajsa-Lotta Georgii Hellberg; Andreas Estmark; [2019]
   Nyckelord :Nonparametric; Parametric; Monte Carlo Approximation; Inference;

   Sammanfattning : The following essay describes and compares Fisher's Randomization Test and Neyman's average treatment test, with the intention of concluding an easily understood blueprint for the comprehension of the practical execution of the tests and the conditions surrounding them. Focus will also be directed towards the tests' different implications on statistical inference and how the design of a study in relation to assumptions affects the external validity of the results. LÄS MER