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MATH1617: Statistics I

Please ensure you check the module availability box for each module outline, as not all modules will run in each academic year. Each module description relates to the year indicated in the module availability box, and this may change from year to year, due to, for example: changing staff expertise, disciplinary developments, the requirements of external bodies and partners, and student feedback. Current modules are subject to change in light of the ongoing disruption caused by Covid-19.

Type Open
Level 1
Credits 10
Availability Available in 2023/24
Module Cap None.
Location Durham
Department Mathematical Sciences

Prerequisites

  • Normally, A level Mathematics at grade A or better, orequivalent

Corequisites

  • Calculus I (Maths Hons) (MATH1081) or Calculus I (MATH1061) and Probablity I (MATH1597)

Excluded Combinations of Modules

  • Mathematics for Engineers and Scientists (MATH1551), SingleMathematics A (MATH1561), Single Mathematics B (MATH1571) may not be taken with or after thismodule.

Aims

  • To introduce the principles and procedures of frequentist and Bayesian statistics, and illustrate them with canonical examples. This lays the foundations for all subsequent study of statistics.
  • To present frequentist and Bayesian principles as alternative approaches to doing statistics; to compare frequentist and Bayesian procedures and results.
  • To demonstrate the relevance of these principles and procedures to real problems.

Content

  • Introduction: applications; the nature of statistics; two schools of thought: frequentist and Bayesian.
  • Frequentist inference: principles and procedures of frequentist statistics; statistics and sampling distributions, confidence intervals, hypothesis testing; examples.
  • Bayesian inference: principles and procedures of Bayesian statistics; posterior distributions, credible intervals, decisions; examples.
  • Comparison between frequentist and Bayesian inference.
  • Demonstration of how the principles and procedures apply to real problems.

Learning Outcomes

Subject-specific Knowledge:

  • Knowledge of the principles and procedures of both frequentist and Bayesian inference as approaches to doing statistics.
  • Understanding of how to apply these principles and procedures, both in general, and in canonical examples.
  • Knowledge of the strengths and weaknesses of each approach.
  • Knowledge of the similarities and differences between the two approaches.
  • Understanding of the relevance of these principles and procedures to real problems.

Subject-specific Skills:

  • Ability to solve in principle and in practice arange of both routine and more challenging problems instatistics.

Key Skills:

  • Students will have basic mathematical skills in the followingareas: problem solving, modelling, computation.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • Lectures demonstrate what is required to be learned and theapplication of the theory to practical examples.
  • Tutorials provide the practice and support in applying themethods to relevant situations as well as active engagement and feedbackto the learning process.
  • Problem classes show how to solve example problems in an ideal way, revealing also the thought processes behind such solutions.
  • Weekly homework problems provide formative assessment to guide students in the correct development of their knowledge and skills. They are also an aid in developing students' awareness of standardsrequired.
  • The examination provides a final assessment of the achievementof the student.

Teaching Methods and Learning Hours

ActivityNumberFrequencyDurationTotalMonitored
Lectures273 pw in wks 11,12,13,15,17,19; 2 pw in wks 14, 16, 18, 20; (alternating with Problems Classes), 1 revision in wk 211 Hour27 
Tutorials61 pw in wks 12, 14, 16, 18, 20; 1 revision in wk 211 Hour6Yes
Problem classes41 pw in wks 14, 16, 18, 201 Hour4 
Preparation and Reading63 
Total100 

Summative Assessment

Component: Examination Component Weighting: 90%
ElementLength / DurationElement WeightingResit Opportunity
Written examination 2 hours100Yes
Component: Continuous AssessmentComponent Weighting: 10%
ElementLength / DurationElement WeightingResit Opportunity
Weekly written or electronic assignments to be assessed and returned. Other assignments are set for self-study and complete solutions are made available to students. Students will have about one week to complete each assignment. Students will have about one week to complete each assignment. 100Yes

Formative Assessment

More information

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