This course is designed by Raazesh Sainudiin, an Associate Professor in Mathematics with Specialisation in Data Science at the Department of Mathematics, Uppsala University and a Data Science Consultant at Combient AB in Stockholm.


See 1MS926: Applied Statistics for official details.


Statistical hypothesis testing (interpretation with confidence intervals, p-values), estimation methodology (ML and LS estimation), non-parametric methods, correlation analysis, multiple regression (estimation, prediction, diagnostics).


Written examination at the end of the course (4 credits) combined with assignments given during the course (1 hp).

NOTE: Written exam will be in the Computer Laboratory (you will write using keyboard and may also use pencil/paper) and assignments will prepare you for the exam. Attendance will be taken in the Computer Laboratory. See instructions below on how to submit assignments.


The approach will use formal mathematical communication of concepts with concomitant development of computer programs to cover the syllabus for 1MS926: Applied Statistics.

Lectures will build on: Sets, Maps, Functions, Modular Arithmetic, Axiomatic Probability, Conditional probability, constructive understanding of random variables and structures including graphs, Statistics, Likelihood Principle, Decisions (parametric and non-parametric) including hypothesis testing and estimation. Since the course is taught in English we will spend a bit more time revisiting Probability and Random Variables before covering hypothesis tests and estimations.

YouTube Live and Archive

Most lectures are live via HangoutsOnAir in Youtube at this channel and will be archived in this playlist. We are not set up for live interactions online but for face-to-face interactions in the lecture theatres at Uppsala University.

Course Materials

The first computer lab will show you how to do this!

Individual SageMath Jupyter .ipynb Notebooks - add or replace with new or updated notebooks, as they become available to cover target topics including correlation, linear regression and non/parametric hypothesis testing, etc.

Notebooks to be covered are in progress and will be adapted to the students based on face-to-face feedback

Roughly one notebook will be covered per lecture (we have a total of 12 lectures).

English-Swedish Mathematical Glossary

Bookmark or download this Matematisk Ordbok so that you can look-up the Swedish words for mathematical terms you will encounter in this course and others in the future..

This is the GitHub directory containing the SageMath contents for the course:


Assignments will be graded.

How to Submit Assignments?

Four Steps to Submit Assignments as .ipynb SageMath Notebooks

  1. Place the Assignment0x.ipynb notebook in your course folder as/jp/:
    • so you can access data/ directory inside as/jp/ from the Assignment0x.ipynb notebook.
    • Note that x in Assignment0x.ipynb will be 1, 2 and 3 as the course progresses.
    • You can download the Assignment0x.ipynb notebook from the link called “Download Assignment x” under heading Download Assignment and Submit by Deadline.
  2. Follow the instructions in Assignment0x.ipynb notebook carefully starting from the first cell (including your personal number) and run Test cells to see if there are any errors you can fix before submitting it.
  3. Save the completed .ipynb notebook from your Jupyter notebook server by Clicking “File > Download as > Notebook (.ipynb)”.
  4. Send an Email to your instructor’s email address from your email address (NOT other email addresses!) as follows:
    • submit the completed and saved Assignment0x.ipynb notebook “as attachment” to the email
    • In the Subject field of the email write 1MS926 Assignment x, where x is the number of the assignment, i.e. 1, 2 or 3.
    • Hit “Send”.


  • Assignments will be considered unsubmitted if you do NOT strictly adhere to the above four Steps. For example, do NOT send me emails from your addresses or have the wrong string in the Subject field.
  • Late submissions will be noted to ensure fairness for the timeliness of all students. Assignments submitted after the due date will not be graded. You may resubmit your assignment up to three times and your highest scoring submission, i.e., best of up to three Assignment0x.ipynb notebooks will be used for your grade.

Download Assignment and Submit by Deadline

  1. Weeks 4–5: Download Assignment 1
    • Due Date to submit Assignment01.ipynb is Thursday February 07, 2019 at 1800 hours CET
  2. Weeks 6–8: Download Assignment 2
    • Due Date to submit Assignment02.ipynb is Friday March 01, 2019 at 2359 hours CET
  3. Weeks 9–11: Download Assignment 3 - update notebooks 08-12.ipynb and review Sample Exam Problems while doing Assignment 3.
    • Due Date to submit Assignment03.ipynb is Wednesday, March 20, 2019 at 2359 hours CET


This exam will be in the computer lab and your will use the computer to take your exam, including submitting your answers. You are also expected use pencil/paper to do rough work on certain problems by hand before making the move into the computer. Thinking carefully about a complicated problem with pencil and paper first can often save a lot of time, especially when you use a computer!

Time and Place

Exam will be in computer labs Å 4102, Å 4103, Å 4104, Å 6K1107 in Ångström Laboratory from 0800-1300 hours on Thursday March 21 2019 (ics file).

How to prepare for the exam

Doing all the ‘YouTry’s in the lab-lecture 00.ipynb-12.ipynb notebooks regularly (ideally in the classroom along with your instructor) and doing the Assignments before the deadline is the best preparation for the exam.

It is highly likely that you may get a sample exam during your study period to help you prepare better for the exam.

Generally, one will NOT be able to miss all the lectures/labs, YouTrys, assignments and pass the course by “cramming” in the last few days. This course is preparing you to think on your own from first principles.


We will use SageMath locally during face-to-face interactions.

Supplementary Book:

Computer labs

We have SageMath already installed for you in computer labs. Go to computer labs to access SageMath and to work on the assignments. You will learn how to do download and work with the course materials in the form of .ipynb notebooks in the computer lab. It is strongly recommended that you also install SageMath in your laptop or desktop computer for convenience by following the instructions in the next section.

Prepare your laptop on your own

It may be more convenient to install SageMath on your laptop or desktop.

  • Follow the download and installation instructions for your Operating System from the following URL:
  • To test that you have installed correctly do the following:
  1. On a Mac OS X or Unix/Linux system, say you installed sage in a directory inside your home directory called ~/all/software/sage/, then you can see if the following command launches a Jupyter notebook server successfully:

$ ~/all/software/sage/SageMath/sage -n jupyter

  1. Those with Windows should follow the instructions in the following URL and test that the jupyter notebook server launches successfully:

Course on GitHub

The source GitHub directory for the course contents is:

YouTube Video Clips for Setup

  • Step 1: How to download Applied Statistics Course Content for the first time:
    • Watch
    • There will be minor changes for Windows Laptop (right-click to extract
    • On Linux or Mac OSX you can also do $ unzip from Terminal after cd ~/
  • Step 2: How to Download SageMath and set it up on your system: