The course gives an introduction to Probability and Statistics. The course covers Probability Axioms, Random variables, Point and interval estimation, Hypothesis testing, Regression and correlation and an Introduction to practical R. About the course 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 Further information can be found in the University's course catalogue: Probability and Statistics Entry Requirements 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 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 English Language Requirements You must be comfortable studying and learning in English if it is not your first language. Learning Outcomes On completion of this course, you will be able to: 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. How/when will the course be delivered? This is an 11-week online course with live (recorded) sessions, comprising a total of 100 hours of study which includes classes, assessment, and self-study. Assessment is 100% group coursework Course fees and funding Course fees for 23/24 are £1,065. 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. Funding eligibility will be assessed at the point of each application for each course; you may be asked to provide further information if you do not meet the general residence conditions. You can check your likely fee status here: https://www.ed.ac.uk/tuition-fees/fee-status/work-out Please email us at upskilling@ed.ac.uk if you would like to discuss your funding eligibility before applying. Please note that full-time students (including full-time PhD students) are not eligible for funding. What will I receive upon completion? You will receive a certificate of completion after the final assessment date if you have submitted your coursework. How to apply Applications for January 2024 are now closed. Related Courses 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: Degree Finder Contact Us This article was published on 2024-06-06