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Why are important in random variables?
It might help if you specified why WHAT was important in random variables.
Is Statistically independent random variables are uncorrelated and vice versa?
the statistically independent random variables are uncorrelated but the converse is not true ,i want a counter example,
What is the difference between a random variable and random process?
A random process is a sequence of random variables defined over a period of time.
What is non-singular linear transformation?
A non-singular linear transformation is a linear transformation between vector spaces that is both injective (one-to-one) and surjective (onto). This means that it maps distinct vectors in the domain to distinct vectors in the codomain and covers the entire codomain. Mathematically, a linear transformation represented by a matrix is non-singular if its determinant is non-zero, indicating that the inverse of the transformation exists. Non-singular transformations preserve the structure of vector spaces, such as linear combinations and dimensions.
What is a stochastic process?
Stochastic process is also known as a random process. It is a collection of random variables that represent the evolution of some system of random values over time.
How are vectors used in football?
Vectors are one of the any variables used in the calculation of the speed of the ball.
Why are important in random variables?
It might help if you specified why WHAT was important in random variables.
What are basis vectors in a transofrm?
Basis vectors are fundamental vectors in a vector space that define its structure and orientation. In the context of a transformation, they serve as the building blocks from which other vectors can be expressed as linear combinations. When a transformation is applied, the basis vectors are mapped to new vectors, allowing for the representation of the entire vector space in a transformed coordinate system. This concept is crucial in fields like linear algebra and computer graphics, where transformations are frequently utilized.
What has the author Michael O'Flynn written?
Michael O'Flynn has written: 'Probabilities, random variables, and random processes' -- subject(s): Probabilities, Random variables, Signal processing, Stochastic processes
Is Statistically independent random variables are uncorrelated and vice versa?
the statistically independent random variables are uncorrelated but the converse is not true ,i want a counter example,
What is the difference between a random variable and random process?
A random process is a sequence of random variables defined over a period of time.
What is the difference between random variable and random variate?
Random variables is a function that can produce outcomes with different probability and random variates is the particular outcome of a random variable.
What is non-singular linear transformation?
A non-singular linear transformation is a linear transformation between vector spaces that is both injective (one-to-one) and surjective (onto). This means that it maps distinct vectors in the domain to distinct vectors in the codomain and covers the entire codomain. Mathematically, a linear transformation represented by a matrix is non-singular if its determinant is non-zero, indicating that the inverse of the transformation exists. Non-singular transformations preserve the structure of vector spaces, such as linear combinations and dimensions.
ARE All continuous random variables are normally distributed?
YES.
What is the importance of distribution functions to stochastic processes?
Stochastic processes are families of random variables. Real-valued (i.e., continuous) random variables are often defined by their (cumulative) distribution function.
What has the author Wai Wan Tsang written?
Wai Wan Tsang has written: 'Analysis of the square-the-histogram method for generating discrete random variables' -- subject(s): Random variables
What is a monotonic transformation and how does it impact the relationship between variables in a mathematical function?
A monotonic transformation is a mathematical function that preserves the order of values in a dataset. It does not change the relationship between variables in a mathematical function, but it can change the scale or shape of the function.
