Objectives

  • Fresh introduction to basics of Python.
  • Writing functions in Python.
  • Using Numpy library.
  • Solving basic statistical problems using Python.
  • Basic normality test using Chi-squared in Python.

Prerequisites (Before you start)

  • Required: background in basics of Python and Numpy.

Deadline

Friday 25/1/2019 11:59 PM.

1. Registration on Github and Our Classroom

  • Register to the task page. Press Accept this assignment.

2. Working in your assignment

After your clone your assignment to your local machine, you can start working on your assignment by using Jupyter Notebook or Google Colaboratory.

You should find 3 jupyter notebooks:

  1. mathfuns.ipynb, which walks you through writing simple functions in Python, and comparing your output with expected output.
  2. errors.ipynb, which you are required to solve the 2nd question you had in the Midterm using Python.
  3. histograms.ipynb, which requires you to plot histogram of given data and test their normality.

A) Using Jupyter Notebook

Interestingly, there is a big scientific package that is shipped with Python, Spyder IDE, Jupyter Notebooks, scientifice libraries, and others in a single big package, Anaconda!

You can download Anaconda from its official website:

Make sure to download Anaconda compatible with Python 3.7.

B) Using Google Colaboratory

Alternatively, you can open and run the tasks notebooks using Google Colaboratory.

  • Upload the notebooks of your tasks from your local machine.

2. Submitting your task on our classroom

  • After you finish your tasks on either Jupyter notebooks or Google Colaboratory, make sure that the repository files are updated with your solutions.
  • Commit changes on task files, then submit:
$ git commit -a -m "Solving problems"
$ git push origin master