Converting Normal Distribution to Standard Normal

In summary, the problem is asking for the values of 'a' and 'b' that will result in L having a standard normal distribution. In order to solve this, we can use the formula for converting a normal distribution to a standard normal distribution, which is Z=(X-μ)/σ. We also know that the variance, σ2, is equal to 1/24. By setting up equations for each value of X and setting them equal to L, we can see that a=b=4. However, this is not the only possible solution. We can also solve for the mean and variance of L in terms of 'a' and 'b' to find other solutions.
  • #1
Samwise_geegee
6
0

Homework Statement



Let X1,X2,X3 be a random sample from a normal distribution with mean μ≠0 and variance σ2=1/24. What are the values of a and b, respectively, in order for L=aX1+4X2+bX3 to have standard normal distribution?

Homework Equations



σ=1/√24

Converting normal distribution to Standard Z=(X-μ)/σ

The Attempt at a Solution



I tried to set this up by calculating Z for each value of X and setting it equal to L

aX1+4X2+bX3= (X1-μ)/(1/√24) + (X2-μ)/(1/√24) + (X3-μ)/(1/√24)

But doesn't this just mean that a=b=4? I don't really know how to tackle this problem. Any help is appreciated!
 
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  • #2
Samwise_geegee said:

Homework Statement



Let X1,X2,X3 be a random sample from a normal distribution with mean μ≠0 and variance σ2=1/24. What are the values of a and b, respectively, in order for L=aX1+4X2+bX3 to have standard normal distribution?


Homework Equations



σ=1/√24

Converting normal distribution to Standard Z=(X-μ)/σ




The Attempt at a Solution



I tried to set this up by calculating Z for each value of X and setting it equal to L

aX1+4X2+bX3= (X1-μ)/(1/√24) + (X2-μ)/(1/√24) + (X3-μ)/(1/√24)

But doesn't this just mean that a=b=4? I don't really know how to tackle this problem. Any help is appreciated!

What are the mean and variance of L, in terms of 'a' and 'b'?
 

1. What is the difference between a normal distribution and a standard normal distribution?

A normal distribution is a probability distribution that is bell-shaped and symmetrical, with the mean, median, and mode all being equal. A standard normal distribution is a specific type of normal distribution in which the mean is 0 and the standard deviation is 1. This makes it easier to compare and analyze data from different normal distributions.

2. How do you convert a normal distribution to a standard normal distribution?

To convert a normal distribution to a standard normal distribution, you need to calculate the z-score for each data point. The z-score is the number of standard deviations a data point is away from the mean. Once you have calculated the z-scores, you can plot them on a standard normal distribution curve.

3. What is the purpose of converting a normal distribution to a standard normal distribution?

Converting a normal distribution to a standard normal distribution allows for easier comparison and analysis of data from different normal distributions. It also simplifies calculations and makes it easier to interpret the data.

4. Can a normal distribution and a standard normal distribution have the same mean and standard deviation?

Yes, it is possible for a normal distribution and a standard normal distribution to have the same mean and standard deviation. This would mean that the data is already centered around the mean and has a standard deviation of 1, making it a standard normal distribution.

5. How is the standard normal distribution used in statistics?

The standard normal distribution is used in statistics to calculate probabilities and make statistical inferences. It is also used in hypothesis testing and confidence interval calculations. Additionally, many statistical methods and models assume that the data follows a normal distribution, making the standard normal distribution a useful tool for data analysis.

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