6.1: Introduction
\(X \sim N(\mu, \sigma)\)
\(\mu=\) the mean; \(\sigma=\) the standard deviation
6.2: The Standard Normal Distribution
\(Z \sim N(0,1)\)
\(z=\) a standardized value ( \(z\)-score)
mean \(=0\); standard deviation \(=1\)
To find the observed value, \(x\), when the \(z\)-scores is known:
\(x=\mu+(z) \sigma\)
\(z\)-score: \(z=\dfrac{x-\mu}{\sigma}\) or \(z=\dfrac{|x-\mu|}{\sigma}\)
\(Z=\) the random variable for \(Z\)-scores
\(Z \sim N(0,1)\)
6.4: Estimating the Binomial with the Normal Distribution
Normal Distribution: \(X \sim N(\mu, \sigma)\) where \(\mu\) is the mean and \(\sigma\) is the standard deviation.
Standard Normal Distribution: \(Z \sim N(0,1)\).