STAT 2507 Lecture Notes - Lecture 8: Round-Off Error, Preboot Execution Environment, Compact Car
12 Oct 2015
School
Department
Course
Professor
Document Summary
Stat 2507 chapter 6: the normal probability distribution. Continuous random variables can assume infinitely many values corresponding to points on line interval. Examples: heights, weights, length of life of particular product, experimental laboratory error. As # of measurements becomes very large & class widths become very narrow, relative frequency histogram appears like smooth curve (*graphs in lecture slide*) This smooth curve describes probability distribution of continuous random variable. Depth or density of probability, which varies w/ x, may be described by mathematical formula f (x), called probability distribution or probability density function for random variable x. There are many diff types of continuous random variables. We try to pick model that: fits data well, allows us to make best possible inferences using data. Area under the curve: *graph in lecture slide* Area under curve is equal to 1. P( a < x < b) = area under the curve b/w a and b.
