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https://github.com/ludwigandreas/sample_calculator
Little sample calculator written on python using scipy
https://github.com/ludwigandreas/sample_calculator
Last synced: 4 days ago
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Little sample calculator written on python using scipy
- Host: GitHub
- URL: https://github.com/ludwigandreas/sample_calculator
- Owner: LudwigAndreas
- Created: 2023-03-31T13:24:42.000Z (almost 2 years ago)
- Default Branch: master
- Last Pushed: 2023-04-25T18:55:09.000Z (over 1 year ago)
- Last Synced: 2024-11-07T12:47:43.028Z (about 2 months ago)
- Language: Python
- Size: 11.7 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Little sample calculator
Little sample calculator written on python using scipy. It may calculate standard metrics for samples, test one-sample, two-samples and multiple-samples hypotheses.
## Installation
git clone https://github.com/LudwigAndreas/sample_calculator.git
Note that you will need to have the required dependencies installed, as listed in the `requirements.txt` file. You can install them using the following command:
pip install -r requirements.txt
## Usage
```
$ python3 main.py [-h] -s SAMPLES [SAMPLES ...] [-a ALPHA] [-g [GENERAL_AVERAGE ...]]
options:
-h, --help show this help message and exit
-a ALPHA, --alpha ALPHA
set alpha value for tests [α]
-g [GENERAL_AVERAGE ...], --general_average [GENERAL_AVERAGE ...]
set general average or list of general averages if there is multiply samples [σ²]
Required named arguments:
-s SAMPLES [SAMPLES ...], --samples SAMPLES [SAMPLES ...]
file or files that contains list of samples
```
Alternatively, you can start the program using the `start.sh` Bash script provided in the repository. The script will start the program with any command-line arguments you pass to it.
To use the script, make sure you have execute permission by running `chmod +x start.sh`. Then, you can start the program with the desired arguments by running the following command in the terminal:
```
./start.sh [-h] -s SAMPLES [SAMPLES ...] [-a ALPHA] [-g [GENERAL_AVERAGE ...]]
```
## Examples
```
$ python3 main.py -s values_1 -a 0.05
--- Sample ---
a_1 | Размер выборки : 11
x̅_1 | Среднее значение : 13.636
s²_1 | Дисперсия выборки : 5.504
s_1 | Cр. кв. отклонение выборки : 2.346
--- One Sample Test ---
--- T-test ---
H₀: μ₀ = 10
H₁: μ₀ != 10
t_крит | t критическое : 1.812
t_набл | t наблюдаемое : 4.901
p-value | p-value : 0.001
Есть основания для опровержения H₀
```
```
$ python3 main.py -s values_1 values_2 -a 0.05
--- Sample ---
a_1 | Размер выборки : 11
x̅_1 | Среднее значение : 13.636
s²_1 | Дисперсия выборки : 5.504
s_1 | Cр. кв. отклонение выборки : 2.346
--- Sample ---
a_2 | Размер выборки : 9
x̅_2 | Среднее значение : 9.444
s²_2 | Дисперсия выборки : 4.247
s_2 | Cр. кв. отклонение выборки : 2.061
--- Two Sample Test ---
--- F-test ---
H₀: σ₀ = σ₁
H₁: σ₀ ≠ σ₁
k₁ | k₁ : 10
k₂ | k₂ : 8
F_крит | F критическое : 3.347
F_набл | F наблюдаемое : 1.267
Нет оснований для опровержения H₀
--- T-test ---
H₀: μ₀ = μ₁
H₁: μ₀ ≠ μ₁
t_крит | t критическое : 2.101
t_набл | t наблюдаемое : 3.981
Есть основания для опровержения H₀
```
```
$ python3 main.py -s anova_1 anova_2 anova_3 -a 0.05
--- Sample ---
a_1 | Размер выборки : 3
x̅_1 | Среднее значение : 2.0
s²_1 | Дисперсия выборки : 0.667
s_1 | Cр. кв. отклонение выборки : 0.816
--- Sample ---
a_2 | Размер выборки : 3
x̅_2 | Среднее значение : 4.0
s²_2 | Дисперсия выборки : 0.667
s_2 | Cр. кв. отклонение выборки : 0.816
--- Sample ---
a_3 | Размер выборки : 3
x̅_3 | Среднее значение : 6.0
s²_3 | Дисперсия выборки : 0.667
s_3 | Cр. кв. отклонение выборки : 0.816
--- Multiple Sample Test ---
--- One-way ANOVA test ---
H₀: μ₀ = μ₁ = μ₂ = ... = μₙ
H₁: There will be at least one population mean that differs from the rest
x̅ | Общее среднее значение : 4.0
a | Общий размер : 9
SSB | Межгрупповая сумма квадратов : 24.0
SSW | Сумма квадратов внутри групп : 6.0
dfb | Степени свобды между групп : 2
dfw | Степени свобды внутри групп : 6
msb | Средний квадрат отклонения между групп : 12.0
msw | Средний квадрат отклонения внутри групп : 1.0
F_крит | Критическое значение критерия фишера : 5.143
F_наб | Значение критерия фишера : 12.0
Есть основания для опровержения H₀
```
## Contributing
I welcome contributions from anyone who would like to help improve this project. If you'd like to contribute, please follow these guidelines:
* Fork the repository and create your branch from main.
* Write clear, concise code and comments.
* Test your changes thoroughly before submitting a pull request.
* Make sure your code follows the project's coding conventions.
* Ensure that your pull request includes a clear description of the problem or feature, and how it improves the project.
* Wait for one of the maintainers to review your code and provide feedback.
* Once your code has been reviewed and approved, it will be merged into the main branch.
Thank you for your interest in contributing to this project!
## License
This project is licensed under the MIT License - see the LICENSE.txt file for details.
## Acknowledgments
I would like to thank the following individuals and organizations for their contributions to this project:
* Mukhamedjanova Sofia, for providing valuable feedback during the development process.
## Contact
If you have any questions, comments, or feedback about this project, you can reach me at:
* Email: [email protected]
* Telegram: @Ludwig_Andreas
* GitHub: @LudwigAndreas
I would love to hear from you!