This section contains two Python programs designed to calculate the Standard deviation of a set of data points. Each program uses a different library for calculations.
- Program 1 ---> math Library
- Program 2 ---> statistics Library
Standard Deviation is a measure of how spread out the values of a dataset are. It calculates the average distance between each data point and the mean of the dataset. A higher Standard Deviation indicates a wider range of values, while a lower Standard Deviation indicates a more concentrated dataset. It is used to understand the variability and dispersion of data. more information
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| The formula for (Standard Deviation) is as follows: |
| σ = √(Σ(xi - μ)² / N) |
| ---> σ = standard deviation |
| ---> Σ = sum of |
| ---> xi = individual data point |
| ---> μ = mean (average) |
| ---> N = number of data points |
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- Run the program.
- You will be prompted to enter a list of data, separated by spaces.
- Input the desired data points.
- The program will calculate and display the standard deviation.
- Both programs are included in this repository, with separate files for each.