## The Geometric Distribution

Summary The geometric distribution has a single parameter (p) = X ~ Geo(p) Geometric distribution can be written as , where q = 1 – p The mean of the geometric distribution is: The variance of the geometric distribution is: The standard deviation of the geometric distribution is: The geometric distribution are the trails needed … Read more

## The Discrete Uniform Distribution

Summary The values of a discrete random variable are obtained by counting, thus making it known as countable Uniform distribution simply means that when all of the random variable occur with equal probability A random variable with probability density function is the expectation and variance of the data we use the following formulas You must … Read more

## The Central Limit Theorem

Summary The Central Limit Theorem (CLT) basically tells us that the sampling distribution of the sample mean is, at least approximately, normally distributed The Central Limit Theorem is exactly what the shape of the distribution of means will be when repeated samples from a given population are drawn As the sample size increases, the sampling … Read more

## The Binomial Distribution

Summary The formula for binomial distribution is as follows: We write the binomial distribution as X ~ Bin(n, p) E(X) = np variance(X) = npq Standard deviation = Binomial distribution is a discrete probability distribution. It has four major conditions that we need to keep in mind when dealing with binomial distribution. There are fixed … Read more

## Statistics

Statistics is the branch of mathematics used to collect, analyze, interpret, and present data. The purpose of studying statistics is to be able to develop critical and analytic thinking skills. Statistics is further divided into two branches: Descriptive statistics: It deals with describing a set of data graphically Inference statistics: This obtains information about a … Read more

## Skewness

Summary The mean, median and mode are all measures of the center of a set of data. The skewness of the data can be determined by how these quantities are related to one another By studying the shape of the data we can discover the relation between the mean, median and mode Pearson’s first method … Read more