complement and which ones apply Hypothesis Test Coding Empty Array to collect

# Complement and which ones apply hypothesis test

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complement) and which one(s) apply - Hypothesis Test Coding: - Empty Array to collect test statistics - For loop for a lot of repetitions/trials - Generate your test stat and append to the collection array - np.count_nonzero(simulated test stat >= observed test stat) / repetitions to compute p-value
General Test Taking Strategies(cont’d) - Hypothesis Testing: conceptual - Know the definitions of the hypotheses (which one do we simulate under?) - Choose a test statistic that points to your alternative if it’s big, null if it’s small - TVD for distributions of categorical variables - Use A/B testing when you’re looking at 2 different datasets and you want to see if there’s a significant difference between them - Causality/Experiments: - Know: randomised controlled trials, confounding variables - Association does not imply causation - Functions: - Have a name, usually take in arguments, usually return a value - Call a function with parentheses around the arguments - Used for one piece of code to work with different inputs
Coding Practice Histograms Probability Practice Simulation/Hypothesis T/F Questions Multiple Choice Functions A/B Testing Both T/F and multiple choice test causality/recent stats concepts
Coding Practice
Histogram Practice (Midterm Spring 2017)
Probability Practice

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• Fall '17
• Statistics, Null hypothesis, Statistical hypothesis testing, Statistical significance

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