Understanding Normal Distribution in Probability and Statistics

[Analysis]

Sir

Kindly arrange to provide the detailed notes for the following questions.



1. When is it appropriate to use the uniform distribution to describe a random variable X?

2. Why do we compute values when using the normal table? Explain.

3. Explain the meaning of the height of a probability curve over a given point.

4. Explain:
a. what the mean , tells us about a normal curve.
b. what the standard deviation σ, tells us about a normal curve.

5. Explain how to compute Z value corresponding to a value of normality distributed random variable. What does the Z value tell us about the value of the random variable.

Your earliest reply in this regard will be much more appreciated and also useful for me class tutorials.

 

[EnumaElish]

Is this homework?

 

[ZioX]

It sounds like prepatory questions for a tutorial.

 

[EnumaElish]

1. When is it appropriate to use the uniform distribution to describe a random variable X?

When all outcomes have equal probability (in the discrete case).

2. Why do we compute values when using the normal table? Explain.

I do not understand the question.

3. Explain the meaning of the height of a probability curve over a given point.

For a discrete r.v., it is the probability of that outcome. For a continuous r.v., it is the change in probability when that point is included in the outcome set.

4. Explain:
a. what the mean , tells us about a normal curve.

Location parameter.

b. what the standard deviation σ, tells us about a normal curve.

Dispersion parameter.

5. Explain how to compute Z value corresponding to a value of normality distributed random variable. What does the Z value tell us about the value of the random variable.

z = (x - mean)/σ is the value which a standard normal variable has the same probability of being greater (or less) than, as the original normal variable than the x value.

 

[Analysis]

yes. Thanks for ur reply