Summary of basic probability theory Math 218, …

Summary of basic probability theory Math 218, Mathematical Statistics D Joyce, Spring 2016 Sample space. A sample space consists of a un-derlying set , whose elements are called outcomes, a collection of subsets of called events, and a function Pon the set of events, called a probability

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Introduction to Modern Algebra - Clark University

Algebra became more general and more abstract in the 1800s as more algebraic structures were invented. Hamilton (1805{1865) invented quaternions (see section2.5.2) and Grassmann

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Practice Integration Z Math 120 Calculus I - Clark University

Z 3 p 7vdv. Since you can rewrite the integrand as 3 p 7v1=3, therefore its integral is 3 4 3 p 7v4=3 + C: 4. 18. Answer. Z 4 p 5t dt. The integral of 4 p 5 t 1=2 is equal to 8 p 5 t1=2 +C. You could also write that as 8 p t=5 + C. 19. Answer. Z 1 3x2 + 3 dx This integral equals 1 3 arctanx+ C. 20. Answer. Z x4 6x3 + ex p x p x dx.

Covariance and Correlation Math 217 Probability and ...

Correlation. The correlation ˆ XY of two joint variables Xand Y is a normalized version of their covariance. It’s de ned by the equation ˆ XY = Cov(X;Y) ˙ X˙ Y: Note that independent variables have 0 correla-tion as well as 0 covariance. By dividing by the product ˙ X˙ Y of the stan-dard deviations, the correlation becomes bounded ...

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Determinants, part III Math 130 Linear Algebra

2x + 3y 4z = 2 3x 2y + 5z = 7 First, compute the determinant of the 3 3 co-e cient matrix. = 1 1 3 2 3 4 3 2 5 = 54 Next, replace the rst column by the constant vec-tor, and compute that determinant. x = 6 1 3 2 3 4 7 2 5 = 27 Then in the unique solution, x = x= = 1 2. Next, replace the second column by the constant vector, and compute that ...

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Directional derivatives, steepest a ascent, tangent planes ...

normal to the surface. If x is any point in R3, then rf(a) (a x) = 0 says that the vector a x is orthogonal to rf(a), and therefore lies in the tangent plane, and so x is a point on that plane. Example 2 (Continuous, nondi erentiable func-tion). You’re familiar with functions of one vari-able that not continuous everywhere. For example,

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Some linear transformations on R2 Math 130 Linear Algebra

Example 8 (Projections). Consider the 2 2 matrix 1 0 0 0 . It sends the vector x y to the vector x 0 . This particular transformation is a projection from 2-space onto the x-axis that forgets the y-coordinate. Projections have 1-eigenspaces and 0-eigenspaces. What are they for this projection? This projection will map our leaf to the x-axis as ...

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Kernel, image, nullity, and rank Math 130 Linear Algebra

homogeneous system Ax = 0. Furthermore, these two lines are parallel, and the vector 2 4 1=2 3=2 0 3 5shifts the line through the origin to the other line. In summary, for this example, the solution set for the nonhomogeneous equation Ax = b is a line in R3 parallel to the solution space for the homogeneous equation Ax = 0.

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The Eigen-Decomposition: Eigenvalues and Eigenvectors

0 1 0 0 ‚ does not have eigenvalues. Even when a matrix has eigenvalues and eigenvectors, the computation of the eigenvectors and eigenvalues of a matrix requires a large number of computations and is therefore better performed by com-puters. 2.1 Digression: An infinity of eigenvectors for one eigenvalue

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44 Multiplicity of Eigenvalues - IMSA

this matrix is (1 – λ)2, so 1 is a double root of this polynomial. ... columns of S are eigenvectors, we have AS=!!!!! ex 1 ex 2"ex ... eigenvalues, but unfortunately we can’t say much more than that. When there is a basis of eigenvectors, we can diagonalize the matrix. Where there is not,

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Chapter 10 Eigenvalues and Singular Values

Consequently, the three eigenvalues are λ1 = 1, λ2 = 2, and λ3 = 3, and Λ = 1 0 0 0 2 0 0 0 3 . The matrix of eigenvectors can be normalized so that its elements are all integers: X = 1 −4 7 −3 9 −49 0 1 9 . It turns out that the inverse of X also has integer entries: X−1 = 130 43 133 27 9 …

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Lecture 28: Similar matrices and Jordan form

1 1 0 4 1 = 1 0 −4 1 2 9 1 6 = −2 1 −15 6 . In addition, B is similar to Λ. All these similar matrices have the same eigen­ values, 3 and 1; we can check this by computing the trace and determinant of A and B. Similar matrices have the same eigenvalues! In fact, the matrices similar to A are all the 2 by 2 matrices with eigenvalues 3 7 1 7

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Normal Matrices - Texas A&M University

6.1. INTRODUCTION TO NORMAL MATRICES 199 Proof. (a) ⇒(b). If A is normal, then AA∗is Hermitian and therefore unitarily diagonalizable. Thus U∗A ∗AU = D = U∗AA∗U.Also,A, A , A ∗A = AA form a commuting family.This implies that eigenvectors of

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