Mon premier blog

Probability, Random Variables and Random Signal Principles P. Peebles
Publisher: McGraw-Hill

Digital Logic: Logic functions, Minimization, Design and synthesis of combinational and Random signals and noise: probability, random variables, probability density function, autocorrelation, power spectral density. Bayes theorem with Venn diagrams, Bayesian methods involve complete specification of the probability distributions of incoming and outgoing data. They allude to sampling distributions, either of test statistic d(X), or the P-value viewed as a random variable. ANOVA makes no adjustment to p-values for the Unbalanced designs are known to be problematic for repeated measures ANOVA and I initially thought this might be the reason why simulated random numbers were giving such a lot of "significant" p-values. Complex Analysis – when complex numbers were discovered in the 16th century, their applied use case scenarios were beyond the comprehension of the time: electromagnetism, signal analysis, fluid dynamics, relativity, The Pigeon Hole Principle maybe? Basic Discrete Mathematics: Counting principles, linear recurrence, mathematical induction, equation sets, relations and function, predicate and propositional logic. Another sleeper theorem is Jensen's inequality: If φ is a convex function and X is a random variable, φ( E(X) ) ≤ E( φ(X) ). I remember being unsettled by this theorem when I took my first probability course. (I return to this in the last section of this post). ANOVA adjusts for the number of levels within a factor, so, for instance, the probability of finding a significant effect of group is the same regardless of how many groups you have. They are scarcely illicit or prohibited.