STAT 124 Lecture Notes - Lecture 3: Standard Score, Standard Deviation, Random Variable
6 Feb 2018
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Normal probability distributions: the probability distribution of many random variables is a normal distribution. It shows what values the random variable can take and is used to assign probabilities to those values: example, pro(cid:271)a(cid:271)ility distri(cid:271)utio(cid:374) of wo(cid:373)e(cid:374)"s heights, here, because we chose a woman randomly, her height, x, is a random variable. Normal distributions: normal or gaussian distributions are a family of symmetrical, bell shaped density curves defined by a mean (mu) and a standard deviation (sigma), n. 68-95-99. 7 empirical rule: for nearly normally distributed data, about 68% falls within 1 sd of the mean, about 95% falls within 2 sd of the mean, about 99. 7% falls within 3 sd of the mean. Ji(cid:373)"s s(cid:272)ore is ((cid:1006)4 21)/ 5 = 0. 6 standard deviations above the mean. Is the normal distribution with the mean 0 and standard deviation is 1: that is, the standard deviation is n(0,1)
