Module: Organisation, Visualisation, Validation and Presentation of Laboratory Data

Module Specifications..

Current Academic Year 2023 - 2024

Please note that this information is subject to change.

Module Title	Organisation, Visualisation, Validation and Presentation of Laboratory Data
Module Code	CS207
School	School of Chemical Sciences
Module Co-ordinator	Semester 1: Loanda Cumba Semester 2: Loanda Cumba Autumn: Loanda Cumba
Module Teachers	Robert Forster Mercedes Vazques Anthony Reilly Joaquin Klug Loanda Cumba
NFQ level	8	Credit Rating	5
Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

Coursework Only
Array

Description

The purpose of this module is to develop skills in the use of spreadsheets and other relevant tools for the visualisation, analysis and presentation of chemical data. In this module, students will develop knowledge and skills in descriptive statistics and the importance of statistical data for validating results.

Learning Outcomes

1. Apply descriptive statistical methods to quantitatively summarize a chemical data set.
2. Present and compare data in graphical and tabular form.
3. Perform linear regression analysis on chemical data sets.
4. Apply theoretical models so as to linearise data sets.
5. Process data so as to maximise information content.

*Type*	*Hours*	*Description*
Workload	Full-time hours per semester
Workshop	30	Real world and theoretical chemical problems in data analysis, visualisation and presentation will be presented and discussed. Students will then quantitatively analyse a spreadsheet containing data relevant to the problem, fit models and produce presentations of their conclusions.
Independent Study	95	Students conduct background reading and practice preparing spreadsheets, documents and presentation skills. Students also revise key chemistry topics covered in course.
Total Workload: 125

All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml

Indicative Content and Learning Activities

Importing instrumental data
Students will learn how to import, format, analyse and present data generated by a range of instruments.

Calibration curves
Students will learn how to perform a calibration curve and add the corresponding error bars.

Data presentation
Students will learn to properly edit documents in Word (for lab report formatting) and Power Point (for oral presentations).

Descriptive Statistics
Students will use Excel to calculate quantitative descriptive statistics for data sets including mean, standard deviation and standard/relative/absolute error, as well as perform one-tailed & two-tailed tests and F-tests.

Modelling Kinetic Data
Students will linearise first and second order kinetic models, apply these models to experimental data and apply linear regression analysis to determine the rate constants.

Assessment Breakdown
Continuous Assessment	100%	Examination Weight	0%

Type	Description	% of total	Assessment Date
Course Work Breakdown
Completion of online activity	Two Loop short question/MCQ assignments and one end-of-module Loop exam	100%	As required

Reassessment Requirement Type
Resit arrangements are explained by the following categories; 1 = A resit is available for all components of the module 2 = No resit is available for 100% continuous assessment module 3 = No resit is available for the continuous assessment component
This module is category 1

Indicative Reading List

James N. Miller, Jane C. Miller: 2010, Statistics and chemometrics for analytical chemistry, 6th, eBook, Pearson Education M.U.A., Harlow, England,
Robert De Levie: 2001, How to use Excel in analytical chemistry and in general scientific data analysis, e-book, Cambridge University Press, Cambridge; New York.,
Diamond, D. and Hanratty, V.C.A.: 1997, Spreadsheet Applications in Chemistry,, Wiley Interscience, ISBN 0471149872

Other Resources

None

Programme or List of Programmes

AC	BSc in Chemical and Pharmaceutical Sc.
AFU	Age Friendly University Programme
AI	Chemistry with Artificial Intelligence
AS	BSc in Analytical Science
BSSA	Study Abroad (DCU Business School)
BSSAO	Study Abroad (DCU Business School)
EST	BSc in Environmental Science & Tech
HMSA	Study Abroad (Humanities & Soc Science)
HMSAO	Study Abroad (Humanities & Soc Science)
IESA	Study Abroad (Institute of Education)
IESAO	Study Abroad (Institute of Education)
SHSA	Study Abroad (Science & Health)
SHSAO	Study Abroad (Science & Health)

Date of Last Revision

05-FEB-10

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