Normal distribution

• How to Use the Normal Distribution to Find Probabilities
  Learn to use the normal distribution by standardizing values to z-scores, finding cumulative probabilities, and checking whether the model fits.
• How to Determine Sample Size for a Normal Mean
  Calculate sample size for estimating a normal population mean from the confidence level, desired margin of error, and standard deviation.
• What Is the Difference Between the Rician and Gaussian Distributions?
  A Rician variable is the magnitude of a Gaussian vector with a possible nonzero mean; compare its support, density, limiting cases, and uses.
• How to Find a Gaussian Classifier’s Decision Boundary
  For Gaussian class-conditional data, derive the Bayes decision boundary from class means, covariances, and priors, and see when it is linear or quadratic.
• Continuity Correction vs. Confidence Interval: What’s the Difference?
  A continuity correction improves normal approximations to discrete probabilities; a confidence interval estimates an unknown parameter. Here is when each applies.
• What Is the Fisher Information of a Normal Distribution?
  For n independent normal observations, the Fisher information is diagonal: n/σ² for the mean and n/(2σ⁴) for the variance.
• Given the Mean and Standard Deviation, How Do You Find a Probability?
  Convert values to z-scores and use the standard normal table to find P(X < b), P(X > a) and P(a < X < b) from a mean and standard deviation, with examples.