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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2023/2024

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DRPS : Course Catalogue : School of Philosophy, Psychology and Language Sciences : Language Sciences

Undergraduate Course: Statistics and Quantitative Methods (Semester 1) (LASC10118)

Course Outline
SchoolSchool of Philosophy, Psychology and Language Sciences CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 10 (Year 3 Undergraduate) AvailabilityAvailable to all students
SCQF Credits20 ECTS Credits10
SummaryThis course is an introduction to study design, statistics and quantitative data analysis as commonly employed in linguistics, using the R software.
Course description The course will cover the basics of statistics and quantitative data analysis, and how to design studies that effectively address the intended research questions. Students will learn the principles of data visualisation and statistical modelling and develop the practical skills necessary to perform such analyses. The course will draw examples from different branches of linguistics and will provide students with hands-on experience in open science practices.

The course will teach students how to carry out statistical inference using Null Hypothesis Significance Testing and how to correctly interpret p-values and confidence intervals.

Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Students MUST NOT also be taking Statistics and Quantitative Methods (Semester 2) (LASC10119)
Other requirements None
Information for Visiting Students
Pre-requisitesVisiting students should have completed at least 3 Linguistics/Language Sciences courses at grade B or above . We will only consider University/College level courses.
High Demand Course? Yes
Course Delivery Information
Not being delivered
Learning Outcomes
On completion of this course, the student will be able to:
  1. Demonstrate an understanding of the difference between descriptive and inferential statistics
  2. Critically evaluate study designs and statistical analyses
  3. Perform a range of statistical analyses with a widely-used statistical software package
  4. Present the results of statistical analyses in a clear and comprehensible way
Reading List
None
Additional Information
Graduate Attributes and Skills Not entered
KeywordsNot entered
Contacts
Course organiserDr Stefano Coretta
Tel:
Email: s.coretta@ed.ac.uk
Course secretaryMr Liam Hedley
Tel: (0131 6)50 9870
Email: liam.hedley@ed.ac.uk
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