STAT 1000Q Lecture Notes - Lecture 22: Central Limit Theorem, Statistic, Sampling Distribution

• School: UConn
• Department: Statistics
• Course: STAT 1000Q
• Professor: Robert Apruzese

Document Summary

Statistic notes 1000q- lecture #22-final exam review part 1. Calculation and interpretation of and for a discrete rv using the 1-var-stats feature on the ti83/84. Calculation of probabilities using binompdf and binomcdf on the ti-83/84. General properties: bell shaped, symmetric, never touches x-axis. Mean = median so center of bell determined by mean alone, shape of bell determined by sd alone. Calculation of probabilities (areas under the normal curve) for standard and non-standard 2 normal distributions using the normalcdf function on the ti- Calculation of percentage points for standard and non-standard normal distributions using the invnorm function on the ti-83/84. Sampling distribution of the sample mean x : the mean of x is , the mean of the distribution the sample came from. Central limit theorem (clt) if x is the sample mean from a sample of size n from any population with mean and standard deviation, then irrespective of the shape of the distribution of the population.