MATH 1F92 Lecture 12: Math+1F92-+6.1-+Discrete+Probabilities+Fill+in
16 Feb 2017
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Random variable: is a numerical measure of the outcome of a probability experiment, Random variables are usually denoted by capital letters like (cid:370)x(cid:371). There are two types of quantitative data, or random variables. Discrete random variable: every value must be an integer number (-1, Continuous: every value can take on any real integer or fractional number (infinite amount of values) Must follow: (cid:883)(cid:4667) (cid:4666)=(cid:4667)=(cid:883) (cid:884)(cid:4667) (cid:882) (cid:4666)=(cid:4667) (cid:883) to be a probability distribution or probability model. Everything we(cid:371)ve dealt with so far in terms of probabilities, has been using discrete data. Our values of x have only been able to equal integer values. So when we say p(x) occurring, what we are really saying is: X represent the value that the random variable can take on. Imagine we were looking at the sum when rolling 2 dice. Our probability distribution (or model) would look like this:
