MA10211: Probability & statistics 1A
[Page last updated: 03 August 2022]
Academic Year: | 2022/23 |
Owning Department/School: | Department of Mathematical Sciences |
Credits: | 6 [equivalent to 12 CATS credits] |
Notional Study Hours: | 120 |
Level: | Certificate (FHEQ level 4) |
Period: |
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Assessment Summary: | EX 100% |
Assessment Detail: |
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Supplementary Assessment: |
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Requisites: | |
Learning Outcomes: | After taking this unit the students should be able to:
* Apply the axioms and basic laws of probability using proper notation and rigorous arguments. * Solve a variety of problems with probability, including the use of combinations, permutations and standard probability distributions. * Perform common expectation calculations. * Calculate marginal and conditional distributions of discrete random variables from joint distributions. * Calculate and explore the behaviour of sums of independent random variables. |
Aims: | To provide a solid foundation in probability theory that will facilitate further study in probability and statistics. |
Skills: | Numeracy T/F A
Problem Solving T/F A Data Analysis TF/A Written and Spoken Communication F (in tutorials) |
Content: | Sample space, events as sets, unions and intersections.
Axioms and laws of probability. Equally likely events. Sampling methods: with or without ordering and replacement. Conditional probability. Partition Theorem. Bayes' Theorem. Independence of events. Bernoulli trials. Discrete random variables (RVs). Probability mass function (PMF). Bernoulli, Geometric, Binomial and Poisson Distributions. Joint and marginal discrete distributions. Definition of continuous random variables (RVs), cumulative distribution functions (CDFs) and probability density functions (PDFs). Some common continuous distributions including uniform, exponential and normal. Independence of RVs (including joint distribution as a product of marginals), Expectation of RVs. Properties of expectation. Expectation of product of independent RVs. Variance and properties. Standard deviation. Moments Covariance, correlation. Sums of independent random variables. Key application: Random walks. Statement of the law of large numbers. |
Programme availability: |
MA10211 is Compulsory on the following programmes:Department of Economics
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Notes:
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