a confounding variable in which uncontrolled factors affected the dependent variable along with or instead of the independent variable
Discrete Random Variable
random variable with either a fininte(whole) number value or a countable number.
Continuous Random Variable
a variable that can take any numeric value within a range of values (range could be infinite, or bounded at either or both ends)
a mathematical description of a random phenomenon consisting of a sample space and a way of assigning probabilities to events
the sum of the values of a random variable divided by the number of values
A measure of spread within a distribution (the square of the standard deviation).
a measure of variability that describes an average distance of every score from the mean
Changing a random variable by a constant
E(X ± c) = E(X) ± c
Var(X ± c) = Var(X)
E(aX) = aE(x)
Var(aX) = a²Var(X)
(NOT on green sheet)
Adding or subtracting random variables
E(X ± Y) = E(X) ± E(Y) and if X and Y are independent, Var(X ± Y) = Var(X) + Var(Y) (The Pythagorean Theorem of Statistics). Remember Variances Add!!! (NOT on green sheet)
To understand this chapter, first
be able to recognize random variables
understand that random variables must be independent in order to determine the variability of their sum of difference by adding variances
be able to find the probability model for a discrete random variable
know how to find the mean and the variance of a random variable
know how to determine the new mean and standard deviation after adding a constant, multiplying a constant, or adding or subtracting two independent random variables
be able to interpret the meaning of the expected value and standard deviation of a random variable in the proper context.