Standard Deviation of Data Calculator

✖Sum of Squares of Individual Values is the sum of the squared differences between each data point and the mean of the dataset.ⓘ Sum of Squares of Individual Values [Σx²]			+10% -10%
✖Number of Individual Values is the total count of distinct data points in a dataset.ⓘ Number of Individual Values [N]			+10% -10%
✖Sum of Individual Values is the total of all the data points in a dataset.ⓘ Sum of Individual Values [Σx]			+10% -10%

✖Standard Deviation of Data is the measure of how much the values in a dataset vary. It quantifies the dispersion of data points around the mean.ⓘ Standard Deviation of Data [σ]

⎘ Copy

👎

Formula

✖

Standard Deviation of Data

Formula

`"σ" = sqrt(("Σx"^{"2"}/"N")-(("Σx"/"N")^2))`

Example

`"2.5"=sqrt(("85"/"10")-(("15"/"10")^2))`

Calculator

LaTeX

Reset

👍

Download Measures of Dispersion Formulas PDF PDF Image

Standard Deviation of Data Solution

STEP 0: Pre-Calculation Summary

Formula Used

Standard Deviation of Data = sqrt((Sum of Squares of Individual Values/Number of Individual Values)-((Sum of Individual Values/Number of Individual Values)^2))
σ = sqrt((Σx²/N)-((Σx/N)^2))
This formula uses 1 Functions, 4 Variables

Functions Used

sqrt - A square root function is a function that takes a non-negative number as an input and returns the square root of the given input number., sqrt(Number)

Variables Used

Standard Deviation of Data - Standard Deviation of Data is the measure of how much the values in a dataset vary. It quantifies the dispersion of data points around the mean.
Sum of Squares of Individual Values - Sum of Squares of Individual Values is the sum of the squared differences between each data point and the mean of the dataset.
Number of Individual Values - Number of Individual Values is the total count of distinct data points in a dataset.
Sum of Individual Values - Sum of Individual Values is the total of all the data points in a dataset.

STEP 1: Convert Input(s) to Base Unit

Sum of Squares of Individual Values: 85 --> No Conversion Required
Number of Individual Values: 10 --> No Conversion Required
Sum of Individual Values: 15 --> No Conversion Required

STEP 2: Evaluate Formula

Substituting Input Values in Formula

σ = sqrt((Σx²/N)-((Σx/N)^2)) --> sqrt((85/10)-((15/10)^2))

Evaluating ... ...

σ = 2.5

STEP 3: Convert Result to Output's Unit

2.5 --> No Conversion Required

FINAL ANSWER

2.5 <-- Standard Deviation of Data

(Calculation completed in 00.004 seconds)

You are here -

Home » Math » Statistics » Measures of Dispersion » Standard Deviation » Standard Deviation of Data

Credits

Created by Prachi

Kamala Nehru College, University of Delhi (KNC), New Delhi

Prachi has created this Calculator and 50+ more calculators!

Verified by Shweta Patil

Walchand College of Engineering (WCE), Sangli

Shweta Patil has verified this Calculator and 1100+ more calculators!

< 7 Standard Deviation Calculators

Pooled Standard Deviation

Go Pooled Standard Deviation = sqrt((((Size of Sample X-1)*(Standard Deviation of Sample X^2))+((Size of Sample Y-1)*(Standard Deviation of Sample Y^2)))/(Size of Sample X+Size of Sample Y-2))

Standard Deviation of Data

Go Standard Deviation of Data = sqrt((Sum of Squares of Individual Values/Number of Individual Values)-((Sum of Individual Values/Number of Individual Values)^2))

Standard Deviation given Mean

Go Standard Deviation of Data = sqrt((Sum of Squares of Individual Values/Number of Individual Values)-(Mean of Data^2))

Standard Deviation of Sum of Independent Random Variables

Go Standard Deviation of Sum of Random Variables = sqrt((Standard Deviation of Random Variable X^2)+(Standard Deviation of Random Variable Y^2))

Standard Deviation given Coefficient of Variation Percentage

Go Standard Deviation of Data = (Mean of Data*Coefficient of Variation Percentage)/100

Standard Deviation given Coefficient of Variation

Go Standard Deviation of Data = Mean of Data*Coefficient of Variation Ratio

Standard Deviation given Variance

Go Standard Deviation of Data = sqrt(Variance of Data)

Standard Deviation of Data Formula

Standard Deviation of Data = sqrt((Sum of Squares of Individual Values/Number of Individual Values)-((Sum of Individual Values/Number of Individual Values)^2))
σ = sqrt((Σx²/N)-((Σx/N)^2))

What is Standard Deviation in Statistics?

In Statistics, the Standard Deviation is a measure of the amount of variation or dispersion of a set of values. A low standard deviation indicates that the values tend to be close to the mean (also called the expected value) of the set, while a high standard deviation indicates that the values are spread out over a wider range. A useful property of the standard deviation is that, unlike the variance, it is expressed in the same unit as the data. The Standard Deviation of a random variable, sample, statistical population, data set, or probability distribution is defined and calculated as the square root of its variance.

How to Calculate Standard Deviation of Data?

Standard Deviation of Data calculator uses Standard Deviation of Data = sqrt((Sum of Squares of Individual Values/Number of Individual Values)-((Sum of Individual Values/Number of Individual Values)^2)) to calculate the Standard Deviation of Data, Standard Deviation of Data formula is defined as the measure of how much the values in a dataset vary. It quantifies the dispersion of data points around the mean. Standard Deviation of Data is denoted by σ symbol.

How to calculate Standard Deviation of Data using this online calculator? To use this online calculator for Standard Deviation of Data, enter Sum of Squares of Individual Values (Σx²), Number of Individual Values (N) & Sum of Individual Values (Σx) and hit the calculate button. Here is how the Standard Deviation of Data calculation can be explained with given input values -> 5.267827 = sqrt((85/10)-((15/10)^2)).

FAQ

What is Standard Deviation of Data?

Standard Deviation of Data formula is defined as the measure of how much the values in a dataset vary. It quantifies the dispersion of data points around the mean and is represented as σ = sqrt((Σx²/N)-((Σx/N)^2)) or Standard Deviation of Data = sqrt((Sum of Squares of Individual Values/Number of Individual Values)-((Sum of Individual Values/Number of Individual Values)^2)). Sum of Squares of Individual Values is the sum of the squared differences between each data point and the mean of the dataset, Number of Individual Values is the total count of distinct data points in a dataset & Sum of Individual Values is the total of all the data points in a dataset.

How to calculate Standard Deviation of Data?

Standard Deviation of Data formula is defined as the measure of how much the values in a dataset vary. It quantifies the dispersion of data points around the mean is calculated using Standard Deviation of Data = sqrt((Sum of Squares of Individual Values/Number of Individual Values)-((Sum of Individual Values/Number of Individual Values)^2)). To calculate Standard Deviation of Data, you need Sum of Squares of Individual Values (Σx²), Number of Individual Values (N) & Sum of Individual Values (Σx). With our tool, you need to enter the respective value for Sum of Squares of Individual Values, Number of Individual Values & Sum of Individual Values and hit the calculate button. You can also select the units (if any) for Input(s) and the Output as well.

How many ways are there to calculate Standard Deviation of Data?

In this formula, Standard Deviation of Data uses Sum of Squares of Individual Values, Number of Individual Values & Sum of Individual Values. We can use 4 other way(s) to calculate the same, which is/are as follows -

Standard Deviation of Data = sqrt(Variance of Data)
Standard Deviation of Data = (Mean of Data*Coefficient of Variation Percentage)/100
Standard Deviation of Data = sqrt((Sum of Squares of Individual Values/Number of Individual Values)-(Mean of Data^2))
Standard Deviation of Data = Mean of Data*Coefficient of Variation Ratio

Home

FREE PDFs

🔍 Search