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constant solution in the plural range, the number is the number of the equation (the root is calculated by the weight number), so the N-order matrix A has n eigenvalues. 3.2 Solving eigenvalues and eigenvectors Examples: 3.3 properties 1) The characteristic vectors belonging to different eigenvalues are linearly independent. 2)λ3)similarity: is the equivalent matrix before Set A, B are n-order matrices, if there is a full rank matrix p, so that

distribution function are recorded as: φ (x), φ (x)Lemma:Standardized transformationsNormal distribution, as soon as possible the range of normal variables is (-∞,∞), but the probability of falling into (µ-δ,µ+δ) is 68.26% (that is: f (x) in the area of this interval), the probability of falling into (µ-3δ,µ+3δ) is 99.74%, almost affirmative, this is the 3δ law.Upper ª: For a standard normal distribution , if zª satisfies the condition P (x>zª) =ª, then zª is the upper ª sub-site of the standar

Note: This article only records chapter concepts and is used to recall knowledge systems. Reference book "Probability Theory and Mathematical Statistics Fourth Edition".Chapter One basic concept of probability theory random test (with three characteristics) sample space, random event sample space sample point random Event (event) event occurrence basic event inevitable event impossibility event (∅) event re