Chapter 6 - Random Variables Flashcards
probability distribution
gives it’s possible values and their probabilities
random variable
takes numerical values that describe the outcomes of a chance process
discrete random variables
random variable that can take one of a finite number of distinct outcomes
“the number of…”
mean (expected value) of discrete random variable
multiply each value by It’s probability then add all products
continuous random variable
random variable that can take any numerical value within a range of values, the range may be infinite or bounded
“the amount of…”
measures something
if y = a + bx is a linear transformation of the random variable x, then
-probability distribution of Y has the same shape as probability of x if b>0
independent random variables
if x tells us nothing about y and vice verses
center of linear transformation
mew y = bmewx
spread of linear transformation
oy= |b|ox
when we perform several independent trials of the same chance process & record the # of times a certain outcome occurs
binomial setting
BINS
count of X successes in binomial setting
binomial random variable
probability of distribution X with parameters n and p
n = number of trials
p = probability
binomial distribution
use binompdf when
x = k
use binomcdf when
x less than or equal to k
mean of binomial random variable
mewx = np