Solve for a with P(0 < z < a)=0.2 | Math Help

In summary, to solve for a in a question like P(0 < z < a)=0.2, you will need to use a table of normal distribution. If the table gives the value from negative infinity to a, you will need to subtract 1/2 from the table value. To find the probability between two values a and b, you can use the formula P(a< z< b)= P(z< b)- P(z< a).
  • #1
ms. confused
91
0
How would I solve for a on a question like this: P(0 < z < a)=0.2 ?

I know that for a question like P(z < a)= 0.85 I would find the inverse-norm of 0.85 to solve for a. I've tried the same thing for the first question, but of course it doesn't work and I'm out of ideas as to how else I should try and solve it. Could someone please help? o:)
 
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  • #2
I assume you are talking about the normal distribution. How is your table of normal distribution set up? Some of them, for example, the one at
http://people.hofstra.edu/faculty/Stefan_Waner/RealWorld/normaltable.html
give the value under the curve from 0 to a which is exactly what you want.

If your table gives from negative infinity to a, then, since the distribution is symmetric about 0, the value from negative infinity to 0 is 1/2 and you just have to subtract 1/2 from the table value.

In general, with either kind of table, to find P(a< z< b), look up the values for a and b separately and subtractP: P(a< z< b)= P(z< b)- P(z< a).
 
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  • #3


To solve for a in the equation P(0 < z < a) = 0.2, we need to use the inverse-norm function on a calculator. This function will give us the value of z that corresponds to a given probability. In this case, we want to find the value of z that has a probability of 0.2 between 0 and a.

To do this, we can follow these steps:

1. Start by writing the equation as P(z < a) = 0.2. This is because the probability between 0 and a is the same as the probability of being less than a.

2. Use a calculator or a statistical table to find the inverse-norm of 0.2. This will give you the value of z that corresponds to a probability of 0.2.

3. The inverse-norm of 0.2 is approximately -0.84. This means that the z-value that corresponds to a probability of 0.2 is -0.84.

4. Now we can substitute this value into our equation: P(z < a) = 0.2. This gives us the equation P(-0.84 < a) = 0.2.

5. Since we want to solve for a, we can simply add 0.84 to both sides of the equation, giving us P(a) = 0.2 + 0.84.

6. Finally, we can use a calculator to find the inverse-norm of 1.04, which is approximately 1.04. This means that a has a value of approximately 1.04.

Therefore, the solution to the equation P(0 < z < a) = 0.2 is a = 1.04.

In summary, to solve for a in an equation like this, we need to use the inverse-norm function on a calculator or statistical table to find the corresponding z-value, and then substitute it back into the equation to solve for a.
 

Related to Solve for a with P(0 < z < a)=0.2 | Math Help

What does P(0 < z < a)=0.2 mean?

This notation represents the probability of a standard normal random variable falling between 0 and a (a being a specific value) being equal to 0.2. In other words, it is the area under the standard normal curve between 0 and a.

What is a standard normal random variable?

A standard normal random variable is a random variable with a mean of 0 and a standard deviation of 1. It follows a normal distribution and is often denoted by the letter z.

How do I solve for a in P(0 < z < a)=0.2?

To solve for a, you can use a standard normal table or a calculator to find the z-score that corresponds to a probability of 0.2. This z-score can then be converted back to the original value of a using the formula z = (a - mean)/standard deviation.

What is the significance of P(0 < z < a)=0.2?

This probability indicates that there is a 20% chance that a standard normal random variable will fall between 0 and a. It can be used in statistical calculations and hypothesis testing to determine the likelihood of certain events occurring.

Can this notation be applied to other probability distributions?

Yes, this notation can be used for any continuous probability distribution, not just the standard normal distribution. The only difference is that the values of z and a will change depending on the distribution being used.

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