Stats: finding probability in normal distribution

In summary, To find Z0 such that P(z > z0) = 0.1234, you can use the standard normal distribution table to find the closest value (0.1217) which corresponds to 0.31. However, this is for the case when 0 ≤ z ≤ z0. If you are looking for the case when -∞ ≤ z ≤ z0, you can use the table provided in the conversation or find the value 1-P(Z>z0) which corresponds to about z0=1.155.
  • #1
yellowduck
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0

Homework Statement



Find Z0 such that P(z > z0) = 0.1234

Homework Equations



The Attempt at a Solution



Z is the mean which is 0. So if Z0 is less than the mean it should be a negative number. Looking at the table 0.1234 does not show up but the closest is 0.1217 which is 0.31.
So Z0 is -0.31?
 
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  • #2
It depends on if you're saying from [itex]-\infty \leq z \leq z0[/itex] or [itex]0 \leq z \leq z0[/itex]. The value you found is for the latter (+0.31). It sounds like intuitively you are thinking of the former case, but used the table for the latter case.

Here if you needed another table-- http://www.math.unb.ca/~knight/utility/NormTble.htm
 
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  • #3
Z is not the mean, it is the standard normal random variable. You want to find P(Z > z0). So you want to find P(Z<z0) such that it equals to 1-P(Z>z0). 1-0.1234=0.8766, which corresponds to about z0=1.155 from the table David posted
 

1. What is a normal distribution?

A normal distribution, also known as a Gaussian distribution, is a bell-shaped probability distribution that is symmetrical around the mean. It is commonly used to model continuous random variables in statistics.

2. How is probability calculated in a normal distribution?

The probability of a particular value occurring in a normal distribution can be calculated using the z-score formula, which involves finding the difference between the value and the mean, and then dividing by the standard deviation. This z-score can then be converted to a probability using a z-score table or a statistical software.

3. What is the 68-95-99.7 rule in a normal distribution?

The 68-95-99.7 rule, also known as the empirical rule, states that in a normal distribution, approximately 68% of the data falls within one standard deviation of the mean, 95% falls within two standard deviations, and 99.7% falls within three standard deviations.

4. How can we use normal distribution to make predictions?

Normal distribution can be used to make predictions by calculating the probability of a certain event occurring within a specified range of values. For example, if we know the mean and standard deviation of a population, we can use a normal distribution to predict the probability of a random sample falling within a certain range of values.

5. What is the difference between standard normal distribution and normal distribution?

The standard normal distribution is a special case of the normal distribution with a mean of 0 and a standard deviation of 1. It is often used to standardize data in order to make comparisons between different distributions. Normal distribution, on the other hand, can have any mean and standard deviation, and is used to model real-world data.

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