DATA ANALYSIS

Description

This module is intended to introduce basic data handling knowledge and practice combined with introductory programming skills (digital capabilities) to give students confidence in handling chemical data which they can apply to all modules throughout the course (resourcefulness and resilience) and will also provide a basis for future employment (not only in chemistry) where they will need these skills generally (employability). The hands-on workshop approach rather than formal lectures gives them the chance to solve set problems whilst building their confidence. Indicative content includes: Introduction to Basic statistical concepts Analysis of Variance (ANOVA). One-way and Two-way. Complementary to significance tests. Basic and arithmetics. Parametric vs non-parametric statistics. Testing for normality distribution. Regression; Arithmetics or least squares. Errors of the slope and intercept. Estimations of error in quantification and confidence limits. Investigation of outlier in regression, residuals. Graph Plotting and Graphics using current software Examples of applications to current research A presentation on modern robotics and automation in chemistry (Dr Malcolm Crook) Basics of Python programming Assignment, variables Repetition Making decisions Input/output Graphing in a programming language Extended assignment involving writing a python programme to solve a chemical problem To present a selection of modern data handling methods and techniques. To provide the background necessary for students to comprehend and criticise the results of data analysis. To give students the opportunity to carry out and comment on a variety of practical data handling examples. To cover a range of selected topics in a computer programming language. To cover a range of selected topics in robotics and automation. Attributes Developed 001 Confidently carry out and comment on the results of data handing exercises. KCPT 002 Comprehend and analyze the results of data handling exercises. KC 003 Systematically understand the process of computer programming CP 004 Can apply appropriate programming skills to solve data analysis problems. KCP