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Module Code - Title:

MA4605 - CHEMOMETRICS

Year Last Offered:

2022/3

Hours Per Week:

Lecture

2

Lab

1

Tutorial

0

Other

0

Private

7

Credits

6

Grading Type:

N

Prerequisite Modules:

MA4603

Rationale and Purpose of the Module:

To give students a clear understanding of the importance of statistical methods in their work. To introduce students to the most widely used statistical techniques in the chemical process industries. To develop skills in the use of these techniques through actual case studies using statistical software packages

Syllabus:

Hypothesis testing - type I and type II error, one and two-tailed tests, oc curves. Statistical process control - various charts, mean/range, individuals/moving range, cusum charts. Capability studies - capability indices. Correlation and Regression - method of least squares, multiple regression, linear and non-linear models, regression analysis, analysis of residuals. Importance of plotting data. Design of experiments and analysis of variance - one and two way ANOVA, interaction, factorial designs, responses and factors, Plackett-Burman design, response surface methodology.

Learning Outcomes:

Cognitive (Knowledge, Understanding, Application, Analysis, Evaluation, Synthesis)

On completion of this module students should be able to: Determine probabilities based on the Normal distribution Construct confidence intervals and conduct hypothesis tests for mean(s) and variances. Construct appropriate ANOVA tables based on whether a single factor, multiple factors, blocking factors and/or a Latin square design is under investigation and perform post hoc tests. Calculate a contrast table, main effects, sums of squares and ANOVA table for 2^k factorial designs, identify significant factors and optimise the response. Describe, test and model the relationship between two or more quantitative variables. Construct appropriate control charts, test for process control, determine process capability indices.

Affective (Attitudes and Values)

None

Psychomotor (Physical Skills)

None

How the Module will be Taught and what will be the Learning Experiences of the Students:

Lectures and tutorials

Research Findings Incorporated in to the Syllabus (If Relevant):

Prime Texts:

(1997) Statistical analysis methods for chemists ¿ a software based approach ,

Other Relevant Texts:

Miller, J.C., and Miller, J.C. (2005) Statistics and Chemometrics for Analytical Chemistry , Pearson
Box, G.E.P., Hunter, J.S. and Hunter, W.G. (2005) Statistics for Experimenters: Design, Innovation, and Discovery , Wiley

Programme(s) in which this Module is Offered:

Semester - Year to be First Offered:

Autumn - 08/09

Module Leader:

david.osullivan@ul.ie