Wikipedia
Discrete frequency - Discrete Frequency is defined as the frequency with which the samples of a discrete sinusoid occur. Just as in its continuous-time counterpart (see frequency), the discrete time signal has a time axis, conventionally denoted by n. The time variable n, however, has a constraint that its..
Discrete frequency - Discrete Frequency is defined as the frequency with which the samples of a discrete sinusoid occur. Just as in its continuous-time counterpart (see frequency), the discrete time signal has a time axis, conventionally denoted by n. The time variable n, however, has a constraint that..
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discrete random variable Dictionary definition of discrete random ... - Definition of discrete random variable Our online dictionary has ... discrete random variable A random variable whose set of ... Help; Site feedback; Privacy policy; Terms and .....
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Conclusion
We have seen the application of matrices and determinants in solving system of linear equation with three unknown variables. Matrices and determinants are also widely used in solving large system of linear equation. Some of these methods are Gauss-elimination method, G..
Consistency of a system of linear equation
The above discussion leads to find the solution of a system of linear equations in two variables by using Cramer's rule. Cramer's rule suggests the use of determinants to solve a system of linear equations. Let us denote a 1 b 2 - a 2 b 1 (Denominators of x and y in (4) and (5))..
The above discussion leads to find the solution of a system of linear equations in two variables by using Cramer's rule. Cramer's rule suggests the use of determinants to solve a system of linear equations. Let us denote a 1 b 2 - a 2 b 1 (Denominators of x and y in (4) and (5))..Introduction
Arrangement and selection of objects are the central ideas of this chapter on permutations and combinations. They are widely applied in solving problems of probability, genetic engineering and life scienc..
Example 1:
Using matrix method solve the following systems of linear equations 2x - y + z = -3 3x - z = - 8 2x + 6y ..
Is this a continuous or discrete random variable?Random variables describe key things like asset returns. We then use distribution functions to characterize the random variables
STATISTICS: What is a discrete random variable?I apologize a bug in youtube caused a few of my older videos to become static, if it is not fixed soon I will remove the videos - I apologize. This is an introduction to the concept of discrete Random Variables used in Probability theory.
Question : From a single observation of X we wish to test
Ho: X has a Poisson distribution with Mean lambda = 1
Ha: X has a Poisson distribution with mean lambda = 3
For this test, we plan to reject Ho if we observe X >/ 2.
What is the probability of a Type II error?
What is the probability of a Type I error?
HOW do you solve this question? Thanks. How would I calculate the probability? Which formula and parameters should I use? I get it! Thanks guys. What are the answers?
Answer : The critical region is : x >= 2 P(x=k) = e^-lambda (lambda)^k / k! , k=0,1,2,............ P( Type II error) = P( do not reject H0 / lambda=3) We do not reject H0 when x < 2 P( x < 2 / lambda=3) = P(x=0)+P(x=1) with lambda=3 = 0.049787 + 0.1493612 =0.19915 probability of a Type 1 error = P( reject H0 / lambda=1) P( x >=2 / lambda=1) = 1-P(x < 2 / lambda=1) = 1- P(x=0)-P(x=1) = 1-0.36788-0.36788 = 0.26424
Answer : The critical region is : x >= 2 P(x=k) = e^-lambda (lambda)^k / k! , k=0,1,2,............ P( Type II error) = P( do not reject H0 / lambda=3) We do not reject H0 when x < 2 P( x < 2 / lambda=3) = P(x=0)+P(x=1) with lambda=3 = 0.049787 + 0.1493612 =0.19915 probability of a Type 1 error = P( reject H0 / lambda=1) P( x >=2 / lambda=1) = 1-P(x < 2 / lambda=1) = 1- P(x=0)-P(x=1) = 1-0.36788-0.36788 = 0.26424
Question : The age of a person is commonly considered to be a continuous random variable. Could it be considered a discrete random variable instead? And how/why?
Many thanks!
Answer : Discrete (nearly always and with very few exceptions) Why?? Age to drive [discrete] Age to vote [discrete] Age for collecting Social Secuirty benefits [discrete] Age at death [discrete] Age at marriage [discrete] Age on Driver's Licence [discrete]
Answer : Discrete (nearly always and with very few exceptions) Why?? Age to drive [discrete] Age to vote [discrete] Age for collecting Social Secuirty benefits [discrete] Age at death [discrete] Age at marriage [discrete] Age on Driver's Licence [discrete]