STAT 101 Lecture Notes - Lecture 12: Central Limit Theorem, Random Variable, Standard Deviation
Document Summary
Stat 101 - introduction to business statistics - lecture 12: the normal distribution. The shape of the distribution (bell curve) It is characterized by its mean, , and variance, 2. If you know this, you can create the entire distribution. How to calculate certain probabilities, as prescribed by the empirical rule. We have seen that both binomial and poisson distributions start to look normally distributed: For the binomial, when n gets large. For the poisson, when , the rate, gets large. This convergence to normality, can be explained with the central limit theorem. Probabilities for a normal random variable are calculated by finding the area under this curve. Because we don"t use integration, we can instead use pre-calculated values, aka the z- table (or calculator) The mean controls the location of the center of the distribution. The mean, can take on any value between and + . The variance, 2 controls how spread out the distribution is.
