Determine whether the value is a discrete random variable, continuous random variable, or not a random variable.

The expected value of a discrete random variable always corresponds to an actual outcome that may occur.

According to a survey, 30% of college students said that they spend too much time on Facebook. Suppose this result holds true for the current population of all college students. A random sample of six college students is selected. a. Define the random variable X b. X takes on what values?X = ..................................................... c. Determine the number of trials n and the probability of success for this binomial distribution. d.Find the probability that exactly three of these six college students will say that they will spend too much time on Facebook. Round your answer to three decimal places.

Explain what it means for two random variables to be independent, both mathematically and in layman’s terms. If we assume two random variables are independent, what does it allow us to simplify?

a pair of dice is stimultaneously tossed.  Find the probabilty that the sum of the outcomes is an even number , the probabilty that the sum of the outcomes is at least 8                                                                         the probabilty that the sum of the outcomes is an odd number or a number less than 6        write the probability distribution of the random variable x representing the sum of the outcomes

Imagine that you are training to run a half-marathon and so every week you have 2 intense days, 3 light days, and 2 rest days. On your intense days you run 16 km, on your light days you run 5 km, and on your rest days you do not run. How would you model your miles run per day as a random variable? (Hint: probability distribution)

describe what it means for two events to be statistically dependent

A description of the distribution of the values of a random variable and their associated probabilities is called a probability distribution random variance random variable expected value

Let X be a chi-squared random variable with 12 degrees of freedom. What is the probability that X is greater than 23? What are the steps to come to this conclusion?

Provide an example of a binomial random variable and explain how each condition for the binomial distribution is fulfilled.