STA261 Final Exam Cheat Sheet Kimberly Glennon-Binomial Distributions/Random Variables : must have 4 things—fixed # of trials (n), each trial must be independent, each trial has 2 outcomes (success or failure), must have a constant probability of success. Can use if np>10 and n(1-p)>10-# of possible outcomes that have exactly x successes out of n: 3! / x!(3-x)! times (1/4) x (3/4) 3-x when n=3 and p=1/4 -M x = np and SD x = SqRoot of np(1-p)-Normal Distributions/Random Variables : standardizing (1,2,3 SDs/68, 95, 99.7 rule) and z-score = (value-mean)/SD-Parameter vs Statistic: P is a number that describes the population; S is a number that is computed from a sample.-Sampling Distributions : focus on difference between values of a variable for a sample and its values for the entire population.-if change sample size n, will change variability. Larger sample sizes have less variability.-SD of all sample proportions is the square root of (p(1-p) / n); Sample Mean (x-bar) is same as population mean.
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