If you have a variable whose distribution is approximately Gaussian (Normal), then the z-score gives the probability of observing a value that is equal to or more extreme. This is usually in the context of testing some hypothesis about the mean of the variable.
A very low probability would suggest that your hypothesis is wrong or that your assumptions about the data are wrong or that you have just had the misfortune of an unlikely event actually happening!
Chat with our AI personalities
If the sample size is less then 30 use the T table, if greater then 30 use the Z table.
z score = (test score - mean score)/SD z score = (87-81.1)/11.06z score = 5.9/11.06z score = .533You can use a z-score chart to calculate the probability from there.
If the Z-Score corresponds to the standard deviation, then the distribution is "normal", or Gaussian.
Go back to the basic data, estimate the sample mean and the standard error and use these to estimate the Z-score.
(527-500)/100= Z-score. Then, you should look at the table for this given Z score