## Mean median mode calculator for grouped data

Mean, median and mode Mean, median, mode are the measures of central tendency. They are also known as averages. Averages are the measures which condense a huge set of numerical data into a single numerical value which is representative of the entire data. They give us an idea about the concentration of the values in …

## Continuous Uniform Distribution Calculator With Examples

Continuous Uniform Distribution Calculator With Examples The continuous uniform distribution is the simplest probability distribution where all the values belonging to its support have the same probability density. It is also known as rectangular distribution. This tutorial will help you understand how to solve the numerical examples based on continuous uniform distribution. Continuous Uniform Distribution …

## Poisson Distribution Calculator With Examples

Poisson Distribution Calculator Poisson distribution calculator helps you to determine the probability and cumulative probabilities for Poisson random variable given the mean number of successes ($\lambda$). Poisson Distribution Calculator Average rate of success ($\lambda$): Number of success (x): Calculate Result Probability : P(X = x) Cumulative Probability : P(X ≤ x) Cumulative Probability : P(X …

## Binomial Distribution Calculator with Step by Step Solution

Binomial distribution Calculator with Step by Step Binomial distribution is one of the most important discrete distribution in statistics. In this tutorial we will discuss about how to solve numerical examples based on binomial distribution. Upon successful completion of this tutorial, you will be able to understand how to calculate binomial probabilities. For the theoretical …

## Bernoulli Distribution Calculator

Bernoulli Distribution Calculator Bernoulli’s Process Calculator can help you to calculate the mean, variance and probability for Bernoulli’s distribution with parameter probability of success $p$. Bernoulli Process Calculator Probability of success (p): Number of success (x): Calculate Result Probability : P(X = x) Mean : E(X) Variance : V(X) Standard Deviation : How to use …

## Chebyshev’s Inequality

Chebyshev’s Inequality Chebyshev’s Inequality is a very powerful inequality, because it applies to any probability distribution. Chebyshev’s Inequality is used to estimate the probability that a random variable $X$ is within $k$ standard deviation of the mean. Before we derive Chebyshev’s Inequality, let us derive the Chebyshev’s Theorem. Chebyshev’s Theorem If $g(x)$ is a non-negative …

## Correlation Coefficient Calculator with Examples

Testing Significance of Linear Relationship A test of significance for a linear relationship between the variables $x$ and $y$ can be performed using the sample correlation coefficient $r_{xy}$. Testing Correlation Coefficient rho = 0 Use Correlation Coefficient calculator for testing significance of correlation coefficient. T test Calculator for testing correlation coefficient   Data 1 : …

## F test calculator for two variances examples

F test for two variances In this tutorial we will discuss some examples on F test for comparing two variances or standard deviations. F test calculator for two variances The F-test calculator for testing two population variances makes it easy to calculate the test statistic, F critical value and the p value given the sample …

## Chi Square Test Calculator for Variance with examples

Chi square test calculator for variance with Examples In this tutorial we will discuss a method for testing a claim made about the population variance $\sigma^2$ or population standard deviation $\sigma$. To test the claim about the population variance or population standard deviation we use chi-square test. We will discuss some numerical examples using six …

## Karl Pearson coefficient of skewness Calculator

Karl Pearson coefficient of skewness for grouped data Let $(x_i,f_i), i=1,2, \cdots , n$ be given frequency distribution. The Karl Pearson’s coefficient skewness is given by $S_k =\dfrac{Mean-Mode}{sd}=\dfrac{\overline{x}-\text{Mode}}{s_x}$ OR $S_k =\dfrac{3(Mean-Median)}{sd}=\dfrac{3(\overline{x}-M)}{s_x}$ where, $\overline{x}$ is the sample mean, $M$ is the median, $s_x$ is the sample standard deviation. Sample mean The sample mean $\overline{x}$ is given …