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LSE: LSEST104b1 Statistics 2 Part 1

COURSE SYLLABUS

STATS 2 Part 1: Probability and Distribution Theory

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Course length: Credit hours: Contact hours:
5 weeks 6.0 12-15 per week

Course Description

This course develops students’ knowledge of probability and distribution theory. The emphasis is on topics that are of importance in applications of econometrics, finance, and social sciences. Concepts and methods that provide the foundation for more specialised courses in statistics are introduced.

Suggested Further Reading

Newbold, P., W. Carlson and B. Thorne Statistics for Business and Economics. (Pearson Education, 2019) ninth edition [ISBN 978-1292315034]

Assessment

This course is assessed by a mixture of online questions, activities, and assignments as well a single, online final exam approximately 1 hour in duration. See below for a detailed breakdown.

Learning Outcomes

  1. Recall probability axioms and important probability results, including Bayes’ theorem, and apply these to a range of problems.
  2. Apply and be competent users of standard statistical operators and be able to recall a variety of well-known distributions and their respective moments.
  3. Demonstrate an understanding that statistical techniques are based on distributional assumptions and the plausibility of such assumptions must be investigated when analysing real problems.

Course Schedule

Module 1

Probability Theory I

Topics:

● Probability Theory

● Set Theory: The Basics, Part One

● Set Theory: The Basics, Part Two

● Axiomatic Definition of Probability

● Classical Probability and Counting Rules

Module 2

Probability Theory II

Topics:

● Conditional Probability and Bayes’ Theorem, Part One

● Conditional Probability and Bayes’ Theorem, Part Two

● Conditional Probability and Bayes’ Theorem, Part Three

● Conditional Probability and Bayes’ Theorem, Part Four

Module 3

Random Variables

Topics:

● Random Variables

● Discrete Random Variables, Part I

● Discrete Random Variables, Part II

● Discrete Random Variables, Part III

● Discrete Random Variables, Part IV

● Continuous Random Variables, Part I

● Continuous Random Variables, Part II

Module 4

Common Distributions of Random Variables

Topics:

● Common Distributions of Random Variables

● Common Discrete Distributions, Part I

● Common Discrete Distributions, Part II

● Common Discrete Distributions, Part III

● Common Continuous Distributions, Part I

● Common Continuous Distributions, Part II

● Common Continuous Distributions, Part III

Module 5

Multivariate Random Variables

Topics:

● Multivariate Random Variables

● Joint Probability Functions

● Marginal Distributions

● Conditional Distributions

● Covariance and Correlation, Part I

● Independent Random Variables

● Sums and Products of Random Variables

Grading Scale

A

90-100%

B

80-89%

C

70-79%

F

Below 70%

Assignment Weighting

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Course Support

Accessibility Support

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