Normal random variables (3rd)

In summary, the homework statement is asking for a real number x that maximizes P(x < Z < x + \alpha)/\Phi(x+\alpha). I got most of the rest of the homework done, but the three I just posted really have me stumped. The Attempt at a Solution states that it seems obvious to the poster that x=0 gives the largest spread, but they are not sure how to find this. They ask for help in finding x, and that someone who has a calculus background can help them. Number Theory is what brought the poster to these boards in the first place!
  • #1
Proggy99
51
0

Homework Statement


Let Z be a standard normal random variable and [tex]\alpha[/tex] be a given constant. Find the real number x that maximizes P(x < Z < x + [tex]\alpha[/tex])/


Homework Equations





The Attempt at a Solution


Looking at the standard normal tables, it seems obvious to me that x=0 gives the largest spread regardless of the value of the constant, but I am not sure how to find this computationally. Can anyone give me a hint on what direction to take? Thanks for any help.

I got most of the rest of the homework done, but the three I just posted really have me stumped.
 
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  • #2
Proggy99 said:

Homework Statement


Let Z be a standard normal random variable and [tex]\alpha[/tex] be a given constant. Find the real number x that maximizes P(x < Z < x + [tex]\alpha[/tex])/


Homework Equations





The Attempt at a Solution


Looking at the standard normal tables, it seems obvious to me that x=0 gives the largest spread regardless of the value of the constant, but I am not sure how to find this computationally. Can anyone give me a hint on what direction to take? Thanks for any help.

I got most of the rest of the homework done, but the three I just posted really have me stumped.

Looking at the level of your other posts, I'm assuming you have a calculus background? If not - sorry.
Note that

[tex]
P(x \le X \le x + \alpha) = \Phi(x+\alpha) - \Phi(x)
[/tex]

If this is maximized then its derivative (with respect to [tex] x [/tex]) is zero. Find the derivative, and work with that.
 
  • #3
statdad said:
Looking at the level of your other posts, I'm assuming you have a calculus background? If not - sorry.
Note that

[tex]
P(x \le X \le x + \alpha) = \Phi(x+\alpha) - \Phi(x)
[/tex]

If this is maximized then its derivative (with respect to [tex] x [/tex]) is zero. Find the derivative, and work with that.

I took the calculus series as a freshman in college 19 years ago. I am struggling through a few higher level courses in my pursuit of a 7-12 integrated mathematics teaching degree. This homework is for an advanced statistics and probability class through independent study at LSU. I have abstract/modern algebra after this and I will have my math prereqs completed. I bought a calculus book to refresh my memory on some things while working through these classes. Number Theory is what brought me to these boards in the first place!

I am going to go see if I can figure it out from what you gave me. Thanks for the hint, I hope!
 

1. What is a normal random variable?

A normal random variable is a type of probability distribution that follows a bell-shaped curve and is commonly used in statistics and probability theory. It is characterized by its mean and standard deviation, and its values can range from negative infinity to positive infinity.

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

A normal random variable differs from other types of random variables in that its probability distribution is symmetric and can be fully described by its mean and standard deviation. Other types of random variables may have different shapes and require more parameters to be fully described.

3. What is the significance of the standard normal distribution in normal random variables?

The standard normal distribution is a specific type of normal distribution with a mean of 0 and a standard deviation of 1. It is often used as a reference for other normal distributions and allows for easier calculations and comparisons between different normal random variables.

4. How are normal random variables used in statistical analysis?

Normal random variables are commonly used in statistical analysis to model real-world data that follows a normal distribution. They can be used to calculate probabilities, make predictions, and test hypotheses about a population.

5. Can a normal random variable have any value?

Yes, a normal random variable can have any value within its range, which is from negative infinity to positive infinity. However, the probability of extreme values decreases as the value moves further away from the mean, following the bell-shaped curve of the normal distribution.

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