 24.6.24.1.97: Find the mean and the variance of the random variable X with probab...
 24.6.24.1.98: Find the mean and the variance of the random variable X with probab...
 24.6.24.1.99: Find the mean and the variance of the random variable X with probab...
 24.6.24.1.100: Find the mean and the variance of the random variable X with probab...
 24.6.24.1.101: Find the mean and the variance of the random variable X with probab...
 24.6.24.1.102: Find the mean and the variance of the random variable X with probab...
 24.6.24.1.103: What is the expected daily profit if a store sells X air conditione...
 24.6.24.1.104: What is the mean life of a light bulb whose life X [hours] has the ...
 24.6.24.1.105: If the mileage (in multiples of 1000 mi) after which a tire must be...
 24.6.24.1.106: What sum can you expect in rolling a fair die 10 times? Do it. Repe...
 24.6.24.1.107: A small filling station is supplied with gasoline every Saturday af...
 24.6.24.1.108: What capacity must the tank in Prob. II have in order that the prob...
 24.6.24.1.109: Let X [cm] be the diameter of bolts in a production. Assume that X ...
 24.6.24.1.110: Suppose that in Prob. 13. a bolt is regarded as being defective if ...
 24.6.24.1.111: For what choice of the maximum possible deviation c from 1.00 cm sh...
 24.6.24.1.112: TEAM PROJECT. Means, Variances, Expectations. (a) Show that E(X  I...
Solutions for Chapter 24.6: Mean and Variance of a Distribution
Full solutions for Advanced Engineering Mathematics  9th Edition
ISBN: 9780471488859
Solutions for Chapter 24.6: Mean and Variance of a Distribution
Get Full SolutionsThis textbook survival guide was created for the textbook: Advanced Engineering Mathematics, edition: 9. Chapter 24.6: Mean and Variance of a Distribution includes 16 full stepbystep solutions. Since 16 problems in chapter 24.6: Mean and Variance of a Distribution have been answered, more than 48767 students have viewed full stepbystep solutions from this chapter. This expansive textbook survival guide covers the following chapters and their solutions. Advanced Engineering Mathematics was written by and is associated to the ISBN: 9780471488859.

Big formula for n by n determinants.
Det(A) is a sum of n! terms. For each term: Multiply one entry from each row and column of A: rows in order 1, ... , nand column order given by a permutation P. Each of the n! P 's has a + or  sign.

CayleyHamilton Theorem.
peA) = det(A  AI) has peA) = zero matrix.

Condition number
cond(A) = c(A) = IIAIlIIAIII = amaxlamin. In Ax = b, the relative change Ilox III Ilx II is less than cond(A) times the relative change Ilob III lib II· Condition numbers measure the sensitivity of the output to change in the input.

Cramer's Rule for Ax = b.
B j has b replacing column j of A; x j = det B j I det A

Dimension of vector space
dim(V) = number of vectors in any basis for V.

Exponential eAt = I + At + (At)2 12! + ...
has derivative AeAt; eAt u(O) solves u' = Au.

Free variable Xi.
Column i has no pivot in elimination. We can give the n  r free variables any values, then Ax = b determines the r pivot variables (if solvable!).

Full row rank r = m.
Independent rows, at least one solution to Ax = b, column space is all of Rm. Full rank means full column rank or full row rank.

Kirchhoff's Laws.
Current Law: net current (in minus out) is zero at each node. Voltage Law: Potential differences (voltage drops) add to zero around any closed loop.

Linear combination cv + d w or L C jV j.
Vector addition and scalar multiplication.

Linearly dependent VI, ... , Vn.
A combination other than all Ci = 0 gives L Ci Vi = O.

Markov matrix M.
All mij > 0 and each column sum is 1. Largest eigenvalue A = 1. If mij > 0, the columns of Mk approach the steady state eigenvector M s = s > O.

Nullspace N (A)
= All solutions to Ax = O. Dimension n  r = (# columns)  rank.

Pascal matrix
Ps = pascal(n) = the symmetric matrix with binomial entries (i1~;2). Ps = PL Pu all contain Pascal's triangle with det = 1 (see Pascal in the index).

Random matrix rand(n) or randn(n).
MATLAB creates a matrix with random entries, uniformly distributed on [0 1] for rand and standard normal distribution for randn.

Reduced row echelon form R = rref(A).
Pivots = 1; zeros above and below pivots; the r nonzero rows of R give a basis for the row space of A.

Row picture of Ax = b.
Each equation gives a plane in Rn; the planes intersect at x.

Row space C (AT) = all combinations of rows of A.
Column vectors by convention.

Standard basis for Rn.
Columns of n by n identity matrix (written i ,j ,k in R3).

Triangle inequality II u + v II < II u II + II v II.
For matrix norms II A + B II < II A II + II B II·