Standard deviation is found in statistics which represents the scattering of data about its mean. The measuring of standard deviation also tells the value of dispersion or variation of a given data set around its mean. Taking the square root of the variance of the given data to evaluate the Standard deviation.
The standard deviation is commonly used in various statistical analyses such as hypothesis testing and confidence interval calculations. Also used in the field of finance to measure the profit or volatility of a stock or investment forum.
In this article, we will discuss the definition of standard deviation, steps to find the standard deviation, its application in different fields, and understanding of the concept of the solution of the standard deviation solve example with detailed steps.
What is Standard deviation?
Standard deviation is statistically measured that shows the dispersion and variation amount in the given data value. It measured how the data spread around the mean. The given data points are shown to be more closely separated around the mean if the value is small and are more widely spread if the standard deviation value is very high. It can be represented by the letter “S.D”.
The decimal/numerical value of the standard deviation is evaluated by taking the square root of the variance. The variance can be measured by the average of the squared deviations of each data point from the mean. For this use the specific formula of the standard deviation.
Formula of Standard deviation
The mathematical formula of standard deviation is different according to the size of the data set or the selection of the data points from the randomly distributed data. The mathematical formula for sample/population is stated as:
For sample data:
S = S.D= √ [∑ (xj – x̄) 2/ (N-1)]
For population data:
σ = S.D= √ [∑ (xj – x̄) 2/ (N)]
Where,
- σ = standard deviation for population data,
- S = standard deviation for sample data.
- Σ = sum of the values for all “j”,
- xj = “jth” value in the given data,
- N = total number,
- x̄ = mean value of the dataset.
Steps to find the Standard Deviation
Follow the below steps to evaluate the standard deviation value for any sample/population data set:
Step 1: Evaluate the Mean: First, find the mean (average) of the data set by summing up all the data points and dividing the total by the number of data points.
Step 2: Find the Deviations: Subtract the mean from each data point to find the deviation of the data set and square each deviation value.
Step 3: Evaluate the Variance: For the variance of the dataset now find the average of the squared deviations by summing them up and dividing by the one less number of data points for the sample data set (while for the population dividing it by the number of population).
Step 4: Find Standard Deviation: To find the standard deviation value take the square root of the variance value.
For a better understanding of the above steps follow the below example.
Example section:
In this section, we will solve the example that helps to understand the method to find standard deviation with the formula.
Example: If the statistical data is 12, 5, 4, 10, and 15 then evaluate the standard deviation of the given sample data set.
Solution:
Step 1: Write the above data in the set form carefully.
Dataset = 5, 4, 10, 12, 15, N = 5, S.D =?
To find the standard deviation first find the variance of the given data. For variance, find the mean and square of deviation.
Step 2: Now, Calculate the mean of the given data points by dividing the sum of data points by the number of data set elements.
x̄ = (∑ xj)/N
x̄ = ∑ (5 + 4 + 10 + 12 +15) /5
x̄ = 46/5
x̄ = 9.2
Step 3: Now evaluate the squared differences from the mean to evaluate the variance of the data set.
(5 – 9.2)2 = (-4.2)2 = 17.64
(4 – 9.2)2 = (-5.2)2 = 27.04
(10 – 9.2)2 = (0.8)2 = 0.64
(12 – 9.2)2 = (2.8)2 = 7.64
(15 – 9.2)2 = (5.8)2 = 33.64
Step 4: Now, Find the Variance by taking the sum of all the above values and dividing by the difference of the total number by one.
V = Variance = (17.64 + 27.04 + 0.64 + 7.64 + 33.64) / (5 – 1)
= (86.8) / 4
V = 21.7
Step 5: Now, take the square root of the variance to find the value of the “S.D.”.
S = √21.7 = 4.66
S = 4.66
To overcome this long calculation process, use the Standard Deviation Calculator to make your calculation faster and save your time. This tool provides the solution of standard deviation for both data sets (sample/population) with detailed steps in a single click, quickly and accurately.
Physical Interpretations of Standard Deviation
The physical interpretation of standard deviation depends on the context of the data being analyzed.
- Measurement Precision: In experimental sciences, the standard deviation represents the measurement precision or the degree of uncertainty associated with the measurements. The small value of the standard deviation indicates the measurements are more precise and consistent and the larger standard deviation shows that there are chances of greater variability and potential errors in the measurements.
- Statistical Models: In Statistical models, Standard deviation plays a crucial role that helps assess the accuracy or goodness-of-fit of a model to the observed data. In regression analysis, the standard deviation of the residuals (the differences between observed and predicted values) provides insights into the variability of the model’s predictions.
Application of Standard Deviation:
- Finance: It is commonly used to measure the risk of a particular stock or portfolio. It helps the investors to understand the potential risk and percentage of return of their investments.
- Quality control: In a manufacturing company, the standard deviation is used to measure the consistency/quality of a product. A lower standard deviation determines that the product is good and on the other hand a higher value of standard deviation shows that the product is not suitable for use.
- Statistical research: Standard deviation is used to measure the dispersion or variation of data in experimental research. It helps researchers to understand whether finding results are statistically significant or not.
Related Blog: Top 5 Calculators Every College Student Needs for Academic Success
Summary:
In this article, we explained the basic definition and formula of standard deviation for sample and population data sets. Also discussed the applications of standard deviation in different fields of science and statistics. For a better understanding of the calculation of standard deviation, I solved a detailed example using the variance with the detailed steps.
The example helps to understand the calculation method and find its value easily. I hope by the proofreading of this article everyone can solve the related problem easily.
Standard deviation is found in statistics which represents the scattering of data about its mean. The measuring of standard deviation also tells the value of dispersion or variation of a given data set around its mean. Taking the square root of the variance of the given data to evaluate the Standard deviation.
The standard deviation is commonly used in various statistical analyses such as hypothesis testing and confidence interval calculations. Also used in the field of finance to measure the profit or volatility of a stock or investment forum.
In this article, we will discuss the definition of standard deviation, steps to find the standard deviation, its application in different fields, and understanding of the concept of the solution of the standard deviation solve example with detailed steps.
What is Standard deviation?
Standard deviation is statistically measured that shows the dispersion and variation amount in the given data value. It measured how the data spread around the mean. The given data points are shown to be more closely separated around the mean if the value is small and are more widely spread if the standard deviation value is very high. It can be represented by the letter “S.D”.
The decimal/numerical value of the standard deviation is evaluated by taking the square root of the variance. The variance can be measured by the average of the squared deviations of each data point from the mean. For this use the specific formula of the standard deviation.
Formula of Standard deviation
The mathematical formula of standard deviation is different according to the size of the data set or the selection of the data points from the randomly distributed data. The mathematical formula for sample/population is stated as:
For sample data:
S = S.D= √ [∑ (xj – x̄) 2/ (N-1)]
For population data:
σ = S.D= √ [∑ (xj – x̄) 2/ (N)]
Where,
- σ = standard deviation for population data,
- S = standard deviation for sample data.
- Σ = sum of the values for all “j”,
- xj = “jth” value in the given data,
- N = total number,
- x̄ = mean value of the dataset.
Steps to find the Standard Deviation
Follow the below steps to evaluate the standard deviation value for any sample/population data set:
Step 1: Evaluate the Mean: First, find the mean (average) of the data set by summing up all the data points and dividing the total by the number of data points.
Step 2: Find the Deviations: Subtract the mean from each data point to find the deviation of the data set and square each deviation value.
Step 3: Evaluate the Variance: For the variance of the dataset now find the average of the squared deviations by summing them up and dividing by the one less number of data points for the sample data set (while for the population dividing it by the number of population).
Step 4: Find Standard Deviation: To find the standard deviation value take the square root of the variance value.
For a better understanding of the above steps follow the below example.
Example section:
In this section, we will solve the example that helps to understand the method to find standard deviation with the formula.
Example: If the statistical data is 12, 5, 4, 10, and 15 then evaluate the standard deviation of the given sample data set.
Solution:
Step 1: Write the above data in the set form carefully.
Dataset = 5, 4, 10, 12, 15, N = 5, S.D =?
To find the standard deviation first find the variance of the given data. For variance, find the mean and square of deviation.
Step 2: Now, Calculate the mean of the given data points by dividing the sum of data points by the number of data set elements.
x̄ = (∑ xj)/N
x̄ = ∑ (5 + 4 + 10 + 12 +15) /5
x̄ = 46/5
x̄ = 9.2
Step 3: Now evaluate the squared differences from the mean to evaluate the variance of the data set.
(5 – 9.2)2 = (-4.2)2 = 17.64
(4 – 9.2)2 = (-5.2)2 = 27.04
(10 – 9.2)2 = (0.8)2 = 0.64
(12 – 9.2)2 = (2.8)2 = 7.64
(15 – 9.2)2 = (5.8)2 = 33.64
Step 4: Now, Find the Variance by taking the sum of all the above values and dividing by the difference of the total number by one.
V = Variance = (17.64 + 27.04 + 0.64 + 7.64 + 33.64) / (5 – 1)
= (86.8) / 4
V = 21.7
Step 5: Now, take the square root of the variance to find the value of the “S.D.”.
S = √21.7 = 4.66
S = 4.66
To overcome this long calculation process, use the Standard Deviation Calculator to make your calculation faster and save your time. This tool provides the solution of standard deviation for both data sets (sample/population) with detailed steps in a single click, quickly and accurately.
Physical Interpretations of Standard Deviation
The physical interpretation of standard deviation depends on the context of the data being analyzed.
- Measurement Precision: In experimental sciences, the standard deviation represents the measurement precision or the degree of uncertainty associated with the measurements. The small value of the standard deviation indicates the measurements are more precise and consistent and the larger standard deviation shows that there are chances of greater variability and potential errors in the measurements.
- Statistical Models: In Statistical models, Standard deviation plays a crucial role that helps assess the accuracy or goodness-of-fit of a model to the observed data. In regression analysis, the standard deviation of the residuals (the differences between observed and predicted values) provides insights into the variability of the model’s predictions.
Application of Standard Deviation:
- Finance: It is commonly used to measure the risk of a particular stock or portfolio. It helps the investors to understand the potential risk and percentage of return of their investments.
- Quality control: In a manufacturing company, the standard deviation is used to measure the consistency/quality of a product. A lower standard deviation determines that the product is good and on the other hand a higher value of standard deviation shows that the product is not suitable for use.
- Statistical research: Standard deviation is used to measure the dispersion or variation of data in experimental research. It helps researchers to understand whether finding results are statistically significant or not.
Related Blog: Top 5 Calculators Every College Student Needs for Academic Success
Summary:
In this article, we explained the basic definition and formula of standard deviation for sample and population data sets. Also discussed the applications of standard deviation in different fields of science and statistics. For a better understanding of the calculation of standard deviation, I solved a detailed example using the variance with the detailed steps.
The example helps to understand the calculation method and find its value easily. I hope by the proofreading of this article everyone can solve the related problem easily.
, How to Calculate Standard Deviation with Example
