Investigation into numpy.random
| Number | Description |
|---|---|
| 1 | Choose a real-world phenomenon that can be measured and for which you could collect at least one-hundred data points across at least four different variables. |
| 2 | Investigate the types of variables involved, their likely distributions, and their relationships with each other |
| 3 | Synthesise/simulate a data set as closely matching their properties as possible |
| 4 | Detail your research and implement the simulation in a Jupyter notebook – the data set itself can simply be displayed in an output cell within the notebook. |
This project concerns an investigation about the random function from the numpy package using jupyter notebook.
For gathering all the necessary information to complete this project I used as an guideline the original SciPy.org documentation in the section of Random Sampling (numpy.random). [1]
From there I have used Jupyter notebook [2] to proceed with my investigation , and in case you require assistance installing and running Jupyter notebook to read this investigation, please follow the instructions on the reference link. [3]
For this project I have chosen a real world scenario about the admittance process of a student in a university and how many students would be accepted by the university out of all the applicants.
To gather data for this project, I have used the numpy.random function to simulate data, using 4 variables related to the acceptance of a student in a University in the USA, this variables are student’s SAT score, followed by academic performance, financial statements and student's references.
After simulating the data, I have explained and simulated the actual process of selecting the approved students out of all the 500 applicants.
[1] https://docs.scipy.org/doc/numpy-1.14.1/reference/routines.random.html
[3] http://jupyter.org/install
All references used for this project have been added in the jupyter notebook