Module: Visualisation & Validation of Laboratory Data

Latest Module Specifications

Current Academic Year 2025 - 2026

Module Title	Visualisation & Validation of Laboratory Data
Module Code	CHM1013 (ITS: CS207)
Faculty	Science & Health	School	Chemical Sciences
NFQ level	8	Credit Rating	5

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

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2. Apply descriptive statistical methods to quantitatively summarize a chemical data set.
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7. Present and compare data in graphical and tabular form.
10. 2
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12. Perform linear regression analysis on chemical data sets.
15. 3
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17. Apply theoretical models so as to linearise data sets.
20. 4
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22. Process data so as to maximise information content.
25. 5

*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

Section Breakdown
CRN	10249	Part of Term	Semester 1
Coursework	100%	Examination Weight	0%
Grade Scale	40PASS	Pass Both Elements	N
Resit Category	RC1	Best Mark	N
Module Co-ordinator	Loanda Cumba	Module Teacher	David O'Connor

Section Breakdown
CRN	11817	Part of Term	Semester 1
Coursework	100%	Examination Weight	0%
Grade Scale	40PASS	Pass Both Elements	N
Resit Category	RC1	Best Mark	N
Module Co-ordinator	Loanda Cumba	Module Teacher	David O'Connor

Type	Description	% of total	Assessment Date
Assessment 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; RC1: A resit is available for both^* components of the module. RC2: No resit is available for a 100% coursework module. RC3: No resit is available for the coursework component where there is a coursework and summative examination element. ^* ‘Both’ is used in the context of the module having a coursework/summative examination split; where the module is 100% coursework, there will also be a resit of the assessment

Pre-requisite	None
Co-requisite	None
Compatibles	None
Incompatibles	None

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.

Indicative Reading List

Books:

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

Articles:
None

Other Resources

None