Introduction to Probability and Statistics
MODULE CODE
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Module Aims
Aim 1
Give students a grounding in the basic concepts and techniques of applied statistics.
Aim 2
Develop students’ critical and analytical skills in discerning the correct and incorrect use of statistics in practice.
Aim 3
Develop students’ skills in solving statistical problems.
Module Content
Data and surveys: Sampling; Questionnaires; Bias, error and precision.
Descriptive Statistics: Measures of location and dispersion; Diagrams and data presentation.
Statistical Inference: Significance testing and confidence intervals (sample means).
Probability: Axioms and interpretations; Addition and multiplication laws; Conditional probability.
Probability Distributions: Binomial, Poisson and Normal.
Further Inference: z-tests, t-tests, paired and unpaired tests, 2-tests.
Correlation and regression: Linear regression and significance tests on r.
Use of statistical packages in analysing data will appear as relevant in the syllabus, with an emphasis on the use of the spreadsheet software Excel.
There will be a strong emphasis throughout the module on the understanding of the context of practical use of statistics.
Learning Outcomes
On successful completion of this module, a student will be able to:
Teaching Methods
The module will be delivered on campus, with weekly lecture/tutorial sessions. Printed notes will be given for each part of the course. Concepts and underlying theory will be explored in the lecture period. Students will learn through a formative process of tackling the exercises at the end of each section, with feedback and extension in tutorials.
In the first semester, students will be taught to use the spreadsheet software Excel to help with their statistical calculations. The material taught in the first semester (data, descriptive statistics, and an introduction to inference) will be tested by a practical assignment using realistic data sets in Excel. In the second semester, the course will be of a more theoretical nature (from the axioms of probability to different inferential tests).
Assessment Methods
This module is assessed through an examination and a written assignment.