Probability and Statistics 1
| Code | School | Level | Credits | Semesters |
| MATH1102 | Mathematical Sciences | 1 | 20 | Full Year UK |
- Code
- MATH1102
- School
- Mathematical Sciences
- Level
- 1
- Credits
- 20
- Semesters
- Full Year UK
Summary
This is a year-long module that introduces students to the mathematics of uncertainty. After a five-week introduction to modelling and simulation, shared with MATH1103 Applied Mathematics, which will include an introduction to probabilistic computation in Python, the module will introduce students to the basic concepts of probability and statistics in a unified manner.
Target Students
Single Honours and Joint Honours students from the School of Mathematical Sciences
Co-requisites
Modules you must take in the same academic year, or have taken in a previous year, to enrol in this module:
Classes
- Eleven 1-hour workshops each week for 3 weeks
- Six 1-hour workshops each week for 6 weeks
- Five 1-hour workshops each week for 4 weeks
Teaching will be through a variety of methods, ranging from traditional lectures and computing sessions through flipped learning, with the delivery tailored to the material on a week-by-week basis.
Assessment
- 40% Coursework 1: Summative assessment based on tasks distributed through the year.
- 40% Exam 1 (2-hour): Written examination. Assessed at the end of the Spring semester.
- 20% Exam 2 (1-hour): Class Test
Assessed by end of spring semester
Educational Aims
The overall aims are to give students an introduction to probability, probabilistic reasoning, statistics and statistical thinking. This provides students with a good foundation for studying more advanced topics in probability and statistics.Learning Outcomes
A student who completes this module successfully should be able to:
L1 State and apply the basic laws and theorems of probability and statistics that underpin modern applications;
L2 Derive point and interval estimators and state and apply the Central Limit Theorem;
L3 Draw connections between probability and statistics;
L4 Conduct appropriate hypothesis tests for a variety of contexts, including calculating distributions of test statistics, p-values and power;
L5 Calculate probabilities, moments and other quantities of interest using mass, density, probability generating functions and joint & conditional mass functions;
L6 Make effective use of statistical software to carry out calculations and interpret the output;
L7 Present hypotheses, methods, results and conclusions verbally or in writing using structured and mathematically rigorous arguments and in a suitable format such as a statistical report.