Probability and Statistics

The course gives an introduction to Probability and Statistics.

• Probability - Axioms; basic laws of probability.

• Random variables - properties; discrete and continuous distributions; central limit theorem.

• Point and interval estimation - Unbiased and consistent estimators; confidence intervals.

• Hypothesis testing - Type I and II errors; p-values; normal and t-tests.

• Regression and correlation - Correlation; linear regression; hypothesis tests; confidence intervals.

• Introduction to practical R

Course organiser: Dr Panagiotis Kaklamanos, Maxwell Institute Research Fellow, School of Mathematics, University of Edinburgh

Probability and Statistics

This course is designed for an interdisciplinary audience, targeting students who undertake programmes in STEM, economics, precision medicine, and other.

This is an introductory Masters-level course (SCQF Level 11). It provides foundational skills and/or an overview of the subject - no prior knowledge is required. Masters-level courses are relatively intensive and require independent learning, critical thinking, analysis, and reflection.

This online course gives an Introduction to Probability and Statistics and covers both theory and practical aspects using the statistical computer package R to perform several statistical analyses. Candidates should have some prior knowledge of Calculus, Combinatorics, Algebra and basic programming knowledge though no prior knowledge of Probability Theory or Statistics is assumed.  Candidate should be educated to a degree level as this course is also catering for those seeking postgraduate academic credit. However, professionals with relevant work experience may also apply even if they do not hold a degree qualification.

Check whether your international qualifications meet our general entry requirements:

Entry requirements by country

You must be comfortable studying and learning in English if it is not your first language.

• Demonstrate a conceptual understanding of fundamental concepts of probability and be able to derive basic results from them.
• Explain their reasoning about probability clearly and precisely, using appropriate technical language.
• Apply statistical techniques to simple problems.
• Interpret the output from statistical analyses.
• Use the statistical computer package R to perform a number of statistical analyses.

This is a 11-week online with live (with recording) sessions course, comprising a total of 100 hours study - classes, assessment and self-study. Online Activities 30, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 68).  Assessment is 100% Group coursework.

There are 11 recorded lectures available online; the online lectures and online exercises last approx 5 weeks, then students work on their final report (40% of the grade) for a couple of weeks. Please note there are no live lectures or sessions.

Course fees for 22/23 are £1010 but funded places are available for people employed or unemployed in Scotland (residency requirements apply).

Funding

Through the Scottish Funding Council (SFC) Upskilling Fund, a limited number of fully-funded places are available on Data Upskilling Short Courses at The University of Edinburgh.

Eligibility

Funded places are available to those who meet SFC fee waiver criteria:

“Courses/provision is open to all Scottish-domiciled/’home fee’ students, which is consistent with SFC’s policy for core funded student places. Students from the rest of the UK (rUK) are not normally considered eligible for SFC funding. If however a university is working with a Scottish/UK employer which has a physical presence or operating in Scotland, rUK employees of that employer would be eligible.”

If you are from outside Scotland, you need to have settled status in the UK and meet other residency criteria:

• be ordinarily resident in the United Kingdom, the Channel Islands or the Isle of Man for the three years immediately before course start date, and
• have ‘settled status’ in the UK (as set out in the Immigration Act 1971) at the course start date, and
• be ordinarily resident in Scotland at the course start date.
• You can find out more about residency criteria on the SAAS website or in this summary.

You will receive a certificate of completion after the final assessment date if you have submitted your coursework.

This course is offered as part of Data Science, Technology and Innovation, a flexible, modular, online programme designed to fully equip tomorrow's data professionals with courses available from across The University of Edinburgh in the sciences, medicine, arts and humanities. You can use credits achieved on this course towards postgraduate study on this programme (MSc, PG Diploma or PG Certificate), subject to approval by the Programme Director.

You may also be able to use credits achieved on this course towards other University of Edinburgh postgraduate programmes, subject to approval by the relevant Programme Director:

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