Statistics for Data Science: Introduction

Programme details

This course begins on the 16 Apr 2027 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 23 Apr 2027, 6.00-7.00pm (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.

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 visit our English language requirements webpage. 

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.

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.

Programme details

This course begins on the 16 Apr 2027 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 23 Apr 2027, 6.00-7.00pm (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.

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. 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.

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. 

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.

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 visit our English language requirements webpage. 

Fees

Module code: O26P823MAZ

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