What kind of random variable

Math Statistics and probability Random variables Discrete random variables. Random variables. Discrete and continuous random variables. Constructing a probability distribution for random variable. Practice: Constructing probability distributions.

Probability models example: frozen yogurt. Practice: Probability models. Deriving the variance of the difference of random variables Opens a modal. Combining random variables Opens a modal. Example: Analyzing distribution of sum of two normally distributed random variables Opens a modal. Example: Analyzing the difference in distributions Opens a modal.

Combining normal random variables Opens a modal. Practice Combining random variables Get 3 of 4 questions to level up! Combining normal random variables Get 3 of 4 questions to level up! Binomial random variables. Binomial variables Opens a modal. Recognizing binomial variables Opens a modal. Binomial distribution Opens a modal. Visualizing a binomial distribution Opens a modal. Binomial probability example Opens a modal. Generalizing k scores in n attempts Opens a modal.

Free throw binomial probability distribution Opens a modal. Graphing basketball binomial distribution Opens a modal. Binompdf and binomcdf functions Opens a modal. Binomial probability basic Opens a modal. Practice Identifying binomial variables Get 3 of 4 questions to level up! Binomial probability formula Get 3 of 4 questions to level up! Calculating binomial probability Get 3 of 4 questions to level up! Binomial mean and standard deviation formulas.

Mean and variance of Bernoulli distribution example Opens a modal. Bernoulli distribution mean and variance formulas Opens a modal. Expected value of a binomial variable Opens a modal.

Variance of a binomial variable Opens a modal. Finding the mean and standard deviation of a binomial random variable Opens a modal. Practice Mean and standard deviation of a binomial random variable Get 3 of 4 questions to level up!

Geometric random variables. A discrete random variable X has a countable number of possible values. Example : Let X represent the sum of two dice. Then the probability distribution of X is as follows:. To graph the probability distribution of a discrete random variable, construct a probability histogram. A continuous random variable X takes all values in a given interval of numbers.

Means and Variances of Random Variables:. The mean of a discrete random variable, X, is its weighted average. Each value of X is weighted by its probability. To find the mean of X, multiply each value of X by its probability, then add all the products. The mean of a random variable X is called the expected value of X. As the number of observations increases, the mean of the observed values, , approaches the mean of the population,.