Normal random variables (2nd)

In summary, the expected value of XcosX, sinX, and X/(1+X^2) is 0 due to the symmetry of their respective graphs. However, to calculate the expected value, we need to use the definition of expected value and integrate each equation with respect to the standard normal distribution.
  • #1
Proggy99
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Homework Statement


Let X be a standard normal random variable. Calculate E(XcosX), E(sinX), and [tex]E\left(\frac{X}{1+X^{2}}\right)[/tex]


Homework Equations





The Attempt at a Solution


I have no idea where to start with this. I am not seeing any connection between it and the chapter reading/examples. Can someone show me how to start on one of them. Thanks.
 
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  • #2
Why not start by writing down what E(X cos X) means from the definition of expected value.
 
  • #3
e(ho0n3 said:
Why not start by writing down what E(X cos X) means from the definition of expected value.

Well, I know that the expected value is the mean, or average, of the possible answers. I also know that xcosx creates a graph that is symmetrically when turned at a 180 degree angle around 0. This tells me that there are positive and negative values that offset each other leaving the answer to be 0. I know that sinx does the same thing, with offsetting values leaving the average of 0. I know that the third equation does the same thing, where 1 offsets -1, 2 offsets -2, and so forth, again leaving 0. So know the expected value of all three equations is 0 from an ability to reason that it is so. But I am not sure how to go about calculating the values as the problem wants me to do.
 

What is a normal random variable?

A normal random variable is a type of continuous probability distribution that is commonly used to model real-world phenomena. It is characterized by a symmetric, bell-shaped curve and is often referred to as a Gaussian distribution.

What are the properties of a normal random variable?

A normal random variable has two main properties: 1) it is continuous, meaning that it can take on any value within a specified range, and 2) it is symmetric, meaning that it is equally likely to take on values above and below its mean.

How is a normal random variable different from other types of random variables?

Unlike other types of random variables, a normal random variable has a specific mathematical formula that describes its distribution. This formula, known as the normal distribution function, allows for the calculation of probabilities and other important statistical measures.

What is the central limit theorem and how does it relate to normal random variables?

The central limit theorem states that the sum of a large number of independent, identically distributed random variables will tend towards a normal distribution. This means that many real-world phenomena can be approximated by a normal random variable, making it a useful tool in statistical analysis.

How is a normal random variable used in scientific research?

Normal random variables are commonly used in scientific research to model and analyze data that is normally distributed. This can include things like measurements of physical characteristics, test scores, and many other types of data. By using normal random variables, scientists can make predictions and draw conclusions about the population from which the data was collected.

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