| Module Title |
Visualisation & Validation of Laboratory Data |
| Module Code |
CHM1013 (ITS: CS207) |
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Faculty |
Chemical Sciences |
School |
Science & Health |
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NFQ level |
8 |
Credit Rating |
5 |
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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.
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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.
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| Workload | Full time hours per semester | | Type | Hours | Description |
|---|
| 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 |
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| Section Breakdown | | CRN | 10249 | Part of Term | Semester 1 | | Coursework | 0% | Examination Weight | 0% | | Grade Scale | 40PASS | Pass Both Elements | Y | | Resit Category | RC1 | Best Mark | N | | Module Co-ordinator | David O'Connor | Module Teacher | Loanda Cumba |
| | Section Breakdown | | CRN | 11817 | Part of Term | Semester 1 | | Coursework | 0% | Examination Weight | 0% | | Grade Scale | 40PASS | Pass Both Elements | Y | | Resit Category | RC1 | Best Mark | N | | Module Co-ordinator | David O'Connor | Module Teacher | Loanda Cumba |
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| Assessment Breakdown |
| Type | Description | % of total | Assessment Date |
|---|
| 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
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Pre-requisite |
None
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Co-requisite |
None |
| Compatibles |
None |
| Incompatibles |
None |
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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
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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.
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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 |
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