Where X is a score from the original normal distribution, μ is the mean of the original normal distribution, and σ is the standard deviation of original normal distribution. Normal distributions can be transformed to standard normal distributions by the formula: However, the actual distribution for a normal random variable to a standard normal distribution can be standardized. Therefore, it's impractical to provide a table of probabilities for each combination of mean and standard deviations. There is an unlimited number of normal distributions, each with a different mean or standard deviation. Below are some confidence intervals for the standard normal distribution: The standard normal distribution is a normal distribution with a mean of 0 and a standard deviation of 1.
The way to get around this problem is to standardize a normal random variable, which involves converting it to a general scale for which probability tables exist. A computer is needed to calculate areas under the graph this is required in order to calculate probabilities. The problem with working with a normal distribution is that its formula is very complicated.
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