Variance in Uniform Distribution Solution

STEP 0: Pre-Calculation Summary
Formula Used
Variance of Data = ((Final Boundary Point of Uniform Distribution-Initial Boundary Point of Uniform Distribution)^2)/12
σ2 = ((b-a)^2)/12
This formula uses 3 Variables
Variables Used
Variance of Data - Variance of Data is the expectation of the squared deviation of the random variable associated with the given statistical data from its population mean or sample mean.
Final Boundary Point of Uniform Distribution - Final Boundary Point of Uniform Distribution is the upper bound of the interval in which the random variable is defined under uniform distribution.
Initial Boundary Point of Uniform Distribution - Initial Boundary Point of Uniform Distribution is the lower bound of the interval in which the random variable is defined under uniform distribution.
STEP 1: Convert Input(s) to Base Unit
Final Boundary Point of Uniform Distribution: 10 --> No Conversion Required
Initial Boundary Point of Uniform Distribution: 6 --> No Conversion Required
STEP 2: Evaluate Formula
Substituting Input Values in Formula
σ2 = ((b-a)^2)/12 --> ((10-6)^2)/12
Evaluating ... ...
σ2 = 1.33333333333333
STEP 3: Convert Result to Output's Unit
1.33333333333333 --> No Conversion Required
FINAL ANSWER
1.33333333333333 1.333333 <-- Variance of Data
(Calculation completed in 00.005 seconds)

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National Institute of Technology (NIT), Jamshedpur
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Uniform Distribution Calculators

Variance in Uniform Distribution
​ LaTeX ​ Go Variance of Data = ((Final Boundary Point of Uniform Distribution-Initial Boundary Point of Uniform Distribution)^2)/12
Continuous Uniform Distribution
​ LaTeX ​ Go Probability of Non Occurrence of Any Event = 1-Probability of Occurrence of Atleast One Event
Discrete Uniform Distribution
​ LaTeX ​ Go Probability of Non Occurrence of Any Event = 1-Probability of Occurrence of Atleast One Event

Variance in Uniform Distribution Formula

​LaTeX ​Go
Variance of Data = ((Final Boundary Point of Uniform Distribution-Initial Boundary Point of Uniform Distribution)^2)/12
σ2 = ((b-a)^2)/12

What is Variance and the importance of Variance in Statistics?

Variance is a statistical tool used to analyze a statistical data. The word Variance is actually derived from the word variety that in terms of statistics means the difference among various scores and readings. Basically it is the expectation of the squared deviation of the associated random variable from its population mean or sample mean. Variance ensures accuracy as more Variance is considered good as compared to the low Variance or absolutely absence of any Variance. Variance in statistics is important as in a measurement it allows us to measure the dispersion of the set of the variables around their mean. These set of the variables are the variables that are being measured or analyzed. The presence of the Variance allows a statistician to draw some meaningful conclusion from the data. The advantage of Variance is that it treats all deviations from the mean as the same regardless of their direction.

How to Calculate Variance in Uniform Distribution?

Variance in Uniform Distribution calculator uses Variance of Data = ((Final Boundary Point of Uniform Distribution-Initial Boundary Point of Uniform Distribution)^2)/12 to calculate the Variance of Data, Variance in Uniform Distribution formula is defined as the expectation of the squared deviation of the random variable associated with a statistical data following uniform distribution, from its population mean or sample mean. Variance of Data is denoted by σ2 symbol.

How to calculate Variance in Uniform Distribution using this online calculator? To use this online calculator for Variance in Uniform Distribution, enter Final Boundary Point of Uniform Distribution (b) & Initial Boundary Point of Uniform Distribution (a) and hit the calculate button. Here is how the Variance in Uniform Distribution calculation can be explained with given input values -> 1.333333 = ((10-6)^2)/12.

FAQ

What is Variance in Uniform Distribution?
Variance in Uniform Distribution formula is defined as the expectation of the squared deviation of the random variable associated with a statistical data following uniform distribution, from its population mean or sample mean and is represented as σ2 = ((b-a)^2)/12 or Variance of Data = ((Final Boundary Point of Uniform Distribution-Initial Boundary Point of Uniform Distribution)^2)/12. Final Boundary Point of Uniform Distribution is the upper bound of the interval in which the random variable is defined under uniform distribution & Initial Boundary Point of Uniform Distribution is the lower bound of the interval in which the random variable is defined under uniform distribution.
How to calculate Variance in Uniform Distribution?
Variance in Uniform Distribution formula is defined as the expectation of the squared deviation of the random variable associated with a statistical data following uniform distribution, from its population mean or sample mean is calculated using Variance of Data = ((Final Boundary Point of Uniform Distribution-Initial Boundary Point of Uniform Distribution)^2)/12. To calculate Variance in Uniform Distribution, you need Final Boundary Point of Uniform Distribution (b) & Initial Boundary Point of Uniform Distribution (a). With our tool, you need to enter the respective value for Final Boundary Point of Uniform Distribution & Initial Boundary Point of Uniform Distribution and hit the calculate button. You can also select the units (if any) for Input(s) and the Output as well.
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