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MATH1597: Probability I

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Type Open
Level 1
Credits 10
Availability Available in 2024/2025
Module Cap None.
Location Durham
Department Mathematical Sciences

Prerequisites

  • A level Mathematics at grade A or better and ASlevel Further Mathematics at grade A or better, orequivalent.

Corequisites

  • Calculus I (Maths Hons) (MATH1081) or Calculus I (MATH1061)

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

  • This module will give an introduction to the mathematics of probability.
  • It will present a mathematical subject of key importance to the real-world ("applied") that is nevertheless based on rigorous mathematical foundations ("pure").
  • It will present students with a wide range of mathematical ideas in preparation for more demanding and specialized material later.
  • A range of topics are treated each at an elementary level to give a foundation of basic concepts, results, and computational techniques.
  • A rigorous approach is expected.

Content

  • Introduction to probability: chance experiments, sample spaces, events, assigning probabilities. Probability axioms and interpretations.
  • Conditional probability: theorem of total probability, Bayes's theorem. Independence of events.
  • Applications of probability: reliability networks, genetics.
  • Random variables: discrete probability distributions and distribution functions, binomial and Poisson distributions, Poisson approximation to binomial, transformations of random variables.
  • Continuous random variables: probability density functions, uniform, exponential, and normal distributions.
  • Joint, marginal and conditional distributions. Independence of random variables.
  • Expectations: expectation of transformations, variance, covariance, conditional expectation, partition theorem for expectations, Markov and Chebyshev inequalities.
  • Limit theorems: Weak law of large numbers, central limit theorem, moment generating functions.

Learning Outcomes

Subject-specific Knowledge:

  • By the end of the module students will:
  • be able to solve a range of both routine and more challenging problems in probability theory.
  • be familiar with the basic mathematical concepts of probability theory.
  • have a broad knowledge of the subject area demonstrated by detailed familiarity with the following topics:
  • set theoretic framework for sample spaces and events, including notions of countable and uncountable sets;
  • event calculus, probability axioms, conditional probability, Bayes's formula, independence of events;
  • discrete and continuous random variables and their distributions, including particular familiarity with the binomial, Poisson, normal and exponential distributions;
  • joint distributions, conditional distributions, and independence of random variables;
  • expected value of a random variable, variance, covariance, and moment generating functions;
  • tail inequalities, the weak law of large numbers, and the central limit theorem.

Subject-specific Skills:

  • Students will have basic mathematical skills in the following areas: modelling, abstract reasoning, numeracy.

Key Skills:

  • Problem solving.

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 the application of the theory to practical examples.
  • Tutorials provide active engagement and feedback to the learning process.
  • Students are expected to develop their knowledge and skills with at least 50 hours of self-study.
  • 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 standards required.
  • Initial diagnostic testing and associated supplementary problems classes fill in gaps related to the wide variety of syllabuses available at Mathematics A-level.
  • The end-of-year written examination provides a rigorous assessment of the mastery of the lecture material.

Teaching Methods and Learning Hours

ActivityNumberFrequencyDurationTotalMonitored
Lectures273 pw in wks 1-3, 5, 7, 9; 2 pw in wks 4, 6, 8, 10; 1 revision in wk 211 Hour27 
Tutorials61 per week in weeks 2, 4, 6, 8, 10 (Term 1), plus 1 revision tutorial in Term 3 1 Hour6Yes
Problems Classes41 pw in wks 4, 6, 8, 101 Hour4 
Support classes91 pw in wks 2-101 Hour9 
Preparation and Reading54 
Total100 

Summative Assessment

Component: Continuous AssessmentComponent Weighting: 10%
ElementLength / DurationElement WeightingResit Opportunity
4 summative assessment assignments during Term 1 100 
Component: ExaminationComponent Weighting: 90%
ElementLength / DurationElement WeightingResit Opportunity
Written examination2 hours100Yes

Formative Assessment

Term 1: Fortnightly written or electronic assignments to be assessed and returned. Other assignments are set for self-study and solutions are made available to students. Students will have about one week to complete each assignment. Term 2: 45 minute collection paper in the beginning of Epiphany term.

More information

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