Statistics for Data Science: Introduction



Overview

This course will introduce statistics to the beginner, covering measures of central tendency, dispersion, probability theory and inferential statistics.

The method of Ordinary Least Squares will be discussed as will the notion of correlation. The theory of probability will be developed including: conditional probability and mutually exclusive events. Discrete and continuous probability distributions will also be investigated and applied to real world problems. Inferential statistics will also be introduced calculating 95% and 99% confidence intervals and performing hypothesis tests. The chi squared distribution will also be applied to contingency tables and to goodness of fit models.

This course combines online study with a weekly 1-hour live webinar led by your tutor. Find out more about how our short online courses are taught.

Programme details

This course begins on the 19 Sep 2025 which is when course materials are made available to students. Students should study these materials in advance of the first live meeting which will be held on 26 Sep 2025, 6:30-7:30pm (UK time).

Week 1: Variables and graphs.

Week 2: Frequency distributions and measures of central tendency.

Week 3: The standard deviation and measures of dispersion.

Week 4: The method of Ordinary Least Squares, correlation coefficients.

Week 5: Elementary probability theory, the normal distribution and confidence intervals.

Week 6: The binomial, normal and Poisson distributions.

Week 7: Sampling theory and the central limit theorem.

Week 8: Statistical estimation theory and hypothesis testing.

Week 9: The chi squared distribution.

Week 10: Contingency tables and the F-distribution.

Certification

Credit Application Transfer Scheme (CATS) points 

Coursework is an integral part of all online courses and everyone enrolled will be expected to do coursework. All those enrolled on an online course are registered for credit and will be awarded CATS points for completing work at the required standard.

See more information on CATS points

Digital credentials

All students who pass their final assignment will be eligible for a digital Certificate of Completion. Upon successful completion, you will receive a link to download a University of Oxford digital certificate. Information on how to access this digital certificate will be emailed to you after the end of the course. The certificate will show your name, the course title and the dates of the course you attended. You will be able to download your certificate or share it on social media if you choose to do so. 

Please note that assignments are not graded but are marked either pass or fail. 

Fees

Description Costs
Course Fee £360.00

Funding

If you are in receipt of a UK state benefit, you are a full-time student in the UK or a student on a low income, you may be eligible for a reduction of 50% of tuition fees. Please see the below link for full details:

Concessionary fees for short courses

Tutor

Dr Vasos Pavlika

Dr Vasos Pavlika is a Associate Professor (Teaching) at UCL and Saturday School lecturer at the LSE. He has been a lecturer in the Department for Continuing Education, Oxford for several years. Vasos also teaches the History of Science and the History of Mathematics  at the Institute of Continuing Education, Cambridge. Vasos is also an Online Tutor at SOAS (University of London in M.Sc modules in Mathematical Finance) an Online Tutor at Goldsmiths College (University of London in B.Sc modules in Computer Science) and an Online Tutor in Mathematics with the Open University. 

Course aims

  • To introduce measures of central tendency.
  • To discuss the theory of probability.
  • To introduce regression and correlation. 
  • To introduce correlation and regression.
  • To introduce probability theory.
  • To discuss the theory of sampling.

Teaching methods

This course takes place over 10 weeks, with a weekly learning schedule and weekly live webinar held on Microsoft Teams. Shortly before a course commences, students are provided with access to an online virtual learning environment, which houses the course content, including video lectures, complemented by readings or other study materials. Any standard web browser can be used to access these materials, but we recommend Google Chrome. Working through these materials over the course of the week will prepare students for a weekly 1-hour live webinar you will share with your expert tutor and fellow students. All courses are structured to amount to 100 study hours, so that on average, you should set aside 10 hours a week for study. Although the course finishes after 10 weeks, all learning materials remain available to all students for 12 months after the course has finished.

All courses are led by an expert tutor. Tutors guide students through the course materials as part of the live interactions during the weekly webinars. Tutors will also provide individualised feedback on your assignments. All online courses are taught in small student cohorts so that you and your peers will form a mutually supportive and vibrant learning community for the duration of the course. You will learn from your fellow students as well as from your tutor, and they will learn from you.

Learning outcomes

By the end of the course students will be expected:

  • to comprehend measures of location and and of dispersion;
  • to understand the method of ordinary least squares;
  • to comprehend inferential statistics.

After attending this course, students will:

  • be able to linearise data and to use regression techniques on data provided
  • be able to solve problems on probability using the Poisson and binomial distributions as well as many other probability distributions;
  • be able to determine confidence intervals and perform hypothesis tests

Assessment methods

You will be set independent formative and summative work for this course. Formative work will be submitted for informal assessment and feedback from your tutor, but has no impact on your final grade. The summative work will be formally assessed as pass or fail.

Application

Please use the 'Book now' button on this page. Alternatively, please complete an enrolment form.

 

Level and demands

Before attending this course, prospective students will:

  • know how to use a scientific calculator;
  • be familiar with elementary statistics e.g. mean, median, mode and range/spread;
  • understand the basics of probability as the theory of chance.

This course is offered at FHEQ Level 4 (i.e. first year undergraduate level), and you will be expected to engage in independent study in preparation for your assignments and for the weekly webinar. This may take the form, for instance, of reading and analysing set texts, responding to questions or tasks, or preparing work to present in class. Our 10-week Short Online Courses come with an expected total commitment of 100 study hours, including those spent in live webinars.

English Language Requirements

We do not insist that applicants hold an English language certification, but warn that they may be at a disadvantage if their language skills are not of a comparable level to those qualifications listed on our website. If you are confident in your proficiency, please feel free to enrol. For more information regarding English language requirements please follow this link: https://www.conted.ox.ac.uk/about/english-language-requirements

IT requirements

Any standard web browser can be used to access course materials on our virtual learning environment, but we recommend Google Chrome. We also recommend that students join the live webinars on Microsoft Teams using a laptop or desktop computer rather than a phone or tablet due to the limited functionality of the app on these devices.

Terms & conditions for applicants and students

Information on financial support