https://padlet.com/mariengallenero2002/ykhzpiiqucfdetxq Random variable is a variable that is used to quantify the outcome of a random experiment. As data can be of two types, discrete and continuous hence, there can be two types of random variables. en-us 2023-04-01 09:27:08 UTC 2026-01-22 18:43:25 UTC hello@padlet.com https://padlet-uploads.storage.googleapis.com/2010993455/8cad908f0f1278ca492a333d9255e548/random_variable_types_1642495625.png mariengallenero2002 https://padlet.com/mariengallenero2002/ykhzpiiqucfdetxq/wish/2540575232 Discrete random variables are random variables, whose range is a countable set. A countable set can be either a finite set or a countably infinite set. A probability distribution is used to determine what values a random variable can take and how often does it take on these values. For instance, in the above example, X is a discrete variable as its range is a finite set ({0, 1, 2}). Another examples of discrete random variables include the number of children in a family, the Friday night attendance at a cinema, the number of patients in a doctor's surgery, the number of defective light bulbs in a box of ten. ]]> 2023-04-01 10:37:12 UTC https://padlet.com/mariengallenero2002/ykhzpiiqucfdetxq/wish/2540575232 mariengallenero2002 https://padlet.com/mariengallenero2002/ykhzpiiqucfdetxq/wish/2540580458 A random variable that represents the number of successes in a binomial experiment is known as a binomial random variable. A binomial experiment has a fixed number of repeated Bernoulli trials and can only have two outcomes, i.e., success or failure. The number of trials is given by n and the success probability is represented by p.]]> 2023-04-01 10:53:48 UTC https://padlet.com/mariengallenero2002/ykhzpiiqucfdetxq/wish/2540580458 mariengallenero2002 https://padlet.com/mariengallenero2002/ykhzpiiqucfdetxq/wish/2540581379 A geometric random variable is a random variable that denotes the number of consecutive failures in a Bernoulli trial until the first success is obtained. The probability of success in a Bernoulli trial is given by p and the probability of failure is 1 - p.

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A Bernoulli random variable is the simplest type of random variable. It can take only two possible values, i.e., 1 to represent a success and 0 to represent a failure.

]]> 2023-04-01 11:07:09 UTC https://padlet.com/mariengallenero2002/ykhzpiiqucfdetxq/wish/2540583815 mariengallenero2002 https://padlet.com/mariengallenero2002/ykhzpiiqucfdetxq/wish/2540584845 A Poisson random variable is used to show how many times an event will occur within a given time period. These events occur independently and at a constant rate. The parameter of a Poisson distribution is given by λ which is always greater than 0.

]]> 2023-04-01 11:11:05 UTC https://padlet.com/mariengallenero2002/ykhzpiiqucfdetxq/wish/2540584845 mariengallenero2002 https://padlet.com/mariengallenero2002/ykhzpiiqucfdetxq/wish/2540608912 A random variable that can take on an infinite number of possible values is known as a continuous random variable. Such a variable is defined over an interval of values rather than a specific value. An example of a continuous random variable is the weight of a person. In general, quantities such as pressure, height, mass, weight, density, volume, temperature, and distance are examples of continuous random variables. The probability that a continuous random variable takes on an exact value is 0 thus, a probability density function is used to describe such a variable. ]]> 2023-04-01 12:25:03 UTC https://padlet.com/mariengallenero2002/ykhzpiiqucfdetxq/wish/2540608912 mariengallenero2002 https://padlet.com/mariengallenero2002/ykhzpiiqucfdetxq/wish/2540611844 An exponential random variable is used to model an exponential distribution which shows the time elapsed between two events. The parameter of an exponential distribution is given by λ. ]]> 2023-04-01 12:33:07 UTC https://padlet.com/mariengallenero2002/ykhzpiiqucfdetxq/wish/2540611844 mariengallenero2002 https://padlet.com/mariengallenero2002/ykhzpiiqucfdetxq/wish/2540613673 A random variable that follows a normal distribution is known as a normal random variable. The parameters of a normal random variable are the mean μ and variance σ^2.

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