Chapter 1 Statistics and Probability

DISCRETE RANDOM VARIABLE - can only take a finite (countable) number of distinct values. Distinct values mean values that are exact and can be represented by non-negative whole numbers.

CONTINUOUS RANDOM VARIABLE - can assume an infinite number of values that can be represented not only by non-negative whole numbers but also by fractions and decimals. These values are often results of measurement.

 $0\le P\left(x\right)\le1$  

 $∑P\left(x\right)=1$  

Multiply the random variable by its corresponding probabilities

Add the products. The sum will be the mean of the discrete probability distribution.

Find the mean

Multiply the square of the random variable by its corresponding probabilities

Add the products. The sum will be the variance.

To get the standard deviation, get the square root of the variance.

 $\sigma^2=∑〖X^2•P(X)-μ^2〗$