Question

w A random variable is: O All of the above O A value that is uncertain or unpredictable O A function defined on the sample space of an experiment such that there is a numerical value of the random variable corresponding to each possible outcome O Assumes some value, the magnitude of which depends on a particular occurrence or outcome of an experiment Which of the following is an example of a discrete random variable? O Inches of rainfall per year in Tucson O Modulus of rupture of timber O The number of floods per year in New York City O Timber strength in N/mm^2 uestion 3 The following three rules describe which type of function? 0

Answer 1

A random variable is a function defined on the sample space of an experiment such that there is a numerical value of the random variable corresponding to each possible outcome. An example of a discrete random variable is the number of floods per year in New York City.

Step-by-step explanation:

A random variable is a function defined on the sample space of an experiment such that there is a numerical value of the random variable corresponding to each possible outcome. Therefore, the correct option is: A function defined on the sample space of an experiment such that there is a numerical value of the random variable corresponding to each possible outcome.

An example of a discrete random variable is the number of floods per year in New York City. It is a countable value that can only take on specific whole numbers (1, 2, 3, etc.).

Answer 2

A random variable is: A value that is uncertain or unpredictable.

An example of a discrete random variable is : The number of floods per year in New York City

A random variable is a variable whose value is subject to chance. It can take on one of many possible values, each with a certain probability. Random variables are used to model a wide variety of phenomena, such as the weather and the stock market.

A discrete random variable is a random variable whose set of possible values is finite or countably infinite. Discrete random variables are often represented as sequences of numbers, with each number representing the probability of the corresponding outcome occurring.