The Law of Large Numbers is a theorem within probability theory that suggests that as a trial is repeated, and more data is gathered, the average of the results will get closer to the expected value. As the name suggests, the law only applies when a large number of observations or tests are considered.| DeepAI
Central Limit Theorem states that the distribution of observation means approaches a normal distribution model as the sample size gets larger.| DeepAI
In short, variance is the measurement of the distance of a set of random numbers from their collective average value.| DeepAI
A Uniform Distribution is a distribution in which there equal probabilities across all the values in the set.| DeepAI
Skewness is a quantifiable measure of how distorted a data sample is from the normal distribution.| DeepAI
A Probability Density Function is a statistical expression used in probability theory as a way of representing the range of possible values of a continuous random variable. The area under the curve represents the interval of which a continuous random variable will fall, and the total area of the interval represents the probability that the variable will occur.| DeepAI
A Poisson Distribution is a statistical distribution used to express the probability of a given number of events occurring within a fixed interval of time or space.| DeepAI
The normal distribution is the most important and most widely used distribution in statistics. It is sometimes called the bell curve or Gaussian distribution, because it has a peculiar shape of a bell. Mostly, a binomial distribution is similar to normal distribution. The difference between the two is normal distribution is continuous.| DeepAI
A discrete random variable is a random variable with a limited and countable set of possible values.| DeepAI
Continuous random variables are variables with an infinite range of possible values, as opposed to discrete variables with defined ranges.| DeepAI
Probability Theory describes probabilities in terms of a probability space, typically assigning a value between 0 and 1, known as the probability measure, and a set of outcomes known as the sample space.| DeepAI
A Probability Distribution is the sum of the probabilities of the events occurring. There are two distinct types of probability distributions, continuous and discrete.| DeepAI