LDSCI4209 Probability and Statistics Course Descriptor

Course Overview

This course is an introduction to probability and statistics that covers the material primarily from a practical perspective, although it adopts a more formal approach for certain aspects. Probability is the mathematical study of uncertainty and chance, and in addition to being worthy of study in its own right, it is also deeply linked to statistics, which concerns the analysis and interpretation of data. Students will learn applications of statistical methods, such as hypothesis testing, in the context of data and social sciences.

Learning Outcomes

On successful completion of the course, students will be able to:

Knowledge and Understanding

Subject Specific Skills

Transferable and Employability Skills

Teaching and Learning

This course has a dedicated Virtual Learning Environment (VLE) page with a syllabus and range of additional resources (e.g. readings, question prompts, tasks, assignment briefs, discussion boards) to orientate and engage students in their studies.

The scheduled teaching and learning activities for this course are:

• Lectures/labs. 40 scheduled hours – typically including induction, consolidation or revision, and assessment activity hours:
  • Version 1:All sessions in the same sized group, or
  • Version 2: most of the sessions in larger groups; some of the sessions in smaller groups

Faculty hold regular ‘office hours’, which are opportunities for students to drop in or sign up to explore ideas, raise questions, or seek targeted guidance or feedback, individually or in small groups.

Students are to attend and participate in all the scheduled teaching and learning activities for this course and to manage their directed learning and independent study.

Indicative total learning hours for this course: 150

Assessment

Both formative and summative assessment are used as part of this course, with purely formative opportunities typically embedded within interactive teaching sessions, office hours, and/or the VLE.

Summative Assessments

Further information about the assessments can be found in the Course Syllabus.

Feedback

Students will receive formative and summative feedback in a variety of ways, written (e.g. marked up on assignments, through email or the VLE) or oral (e.g. as part of interactive teaching sessions or in office hours).

Indicative Reading

Note: Comprehensive and current reading lists are produced annually in the Course Syllabus or other documentation provided to students; the indicative reading list provided below is for a general guide and part of the approval/modification process only.

• Richard J. Larsen and Morris L. Marx. 2015. Introduction to Mathematical Statistics and Its Applications, 5th Edition. Pearson.

Indicative Topics

Note: Comprehensive and current topics for courses are produced annually in the Course Syllabus or other documentation provided to students; the indicative topics provided below are used as a general guide and part of the approval/modification process only.

• Sample space
• Conditional probability
• Random variables
• Discrete and continuous probability distributions for one or more random variables
• Expectation
• Variance
• Probability distributions (e.g., Binomial, Poisson, and Gaussian)
• Law of large numbers
• Central limit theorem
• Hypothesis testing

Version History