Statistical Methods Applied to Chemical Engineering

Code:

L.EQ017

Acronym:

MEAEQ

Keywords
Classification	Keyword
OFICIAL	Mathematics

Instance: 2023/2024 - 2S

Active?	Yes
Responsible unit:	Department of Chemical and Biological Engineering
Course/CS Responsible:	Bachelor in Chemical Engineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
L.EQ	93	Syllabus	2	-	6	58,5	162

Teaching language

Portuguese

Objectives

Framework:
The use of statistical analysis tools is an undeniable advantage for improving processes and product quality.

Specific aims:
- Acquisition of fundamental knowledge in the area of statistics, in particular in descriptive and inferential statistics, enhancing the development of literacy and reasoning in statistics
- Identification and formulation of statistical analysis problems, their analytical and computational resolution (using the R® application) fostering critical thinking.

Learning outcomes and competences

Students should be able to:

• Apply the fundamental concepts in exploratory data analysis.
• Understand the basic concepts of probability and random variables.
• Understand the concept of the sample distribution of a statistic, and describe, in particular, the behavior of the sample mean.
• Understand the foundations for classical inference involving confidence intervals and hypothesis testing.
• Apply the inferential methods in relation to means, variances and proportions.
• Apply and interpret basic modeling techniques for bivariate data and use inference methods in the context of simple linear models.
• Understand the importance of experimental planning for process improvement.
• Use computational tools in statistical analysis
• Understand that statistics suggest conclusions and not certainties
• Value the role that statistics can have in research work.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

Probabilities and Statistics from high school.

Program

1. Descriptive statistics
2. Introduction to the Theory of Probability
3. Discrete and Continuous Random Variables and Probability Distributions
4. Some Important Discrete Probability Distributions
5. Some Important Continuous Probability Distributions
6. Sample Distributions
7. Point and Interval Estimation of Parameters
8. Tests of Hypotheses
9. Simple Linear Regression Model
10. Introduction to the Design of Experiments

Mandatory literature

Douglas C. Montgomery, George C. Runger; Applied Statistics and Probability for Engineers. ISBN: 0-471-17027-5

Complementary Bibliography

Sheldon M. Ross; Introduction to probability and statistics for engineers and scientists. ISBN: 978-0-12-370483-2
Rui Campos Guimarães, José A. Sarsfield Cabral; Estatística. ISBN: 978-84-481-5589-6
Dinis Duarte Pestana, Sílvio Filipe Velosa; Introdução à probabilidade e à estatística. ISBN: 972-31-0954-9
Bento Murteira... [et al.]; Introdução à estatística. ISBN: 978-84-481-6069-2
Carlos Daniel Paulino e João A. Branco; Exercícios de probabilidade e estatística. ISBN: 972-592-180-1

Teaching methods and learning activities

TP - Theoretical-practical classes of 90 + 90 minutes of exposition of the main concepts accompanied by problem solving

L - Laboratory classes of 90 minutes in rooms with computer equipment for solving exercises with or without the use of R + R Commander.

Software

R + R Commander

keywords

Physical sciences > Mathematics > Statistics
Physical sciences > Mathematics > Probability theory
Physical sciences > Mathematics > Applied mathematics > Engineering mathematics

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Exame	75,00
Teste	25,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	99,50
Frequência das aulas	58,50
Total:	158,00

Eligibility for exams

Registered students who obtain a minimum mark of 6 in the distributed assessment component (AD) will obtain attendance.

Students without attendance in the current year or without attendance in previous years will not be able to attend the Normal Season exam.

Students who do not obtain a minimum mark of 6 in the distributed assessment component may attend the exam in the second call, thus obtaining frequency for the CU.

Calculation formula of final grade

The final rating (CF) is calculated by the following formula:

CF = max(0.25 x AD + 0.75 x EF,EF)

wherein:
AD = (Teste1+Teste2)/2
EF = marks obtained Final Exam

Conditions for obtaining approval:

• a minimum score of 6 in the distributed evaluation component (AD)
• a minimum score of 6 in the final exam (EF)

The tests are compulsory for students without previous attendance. Failure to take a test on the set date corresponds to a zero-rating.

The score of the distributed evaluation component from previous years is not maintained. Taking the tests is optional for students with previous attendance. If they intend to take them, the students must inform the teacher in the first week of classes, being this way linked to the new distributed evaluation.

Special assessment (TE, DA, ...)

By examination at the appropriate seasons.

Classification improvement

The improvement in classification will take place in the appeal examination. The calculation formula is identical to the final rating listed above.

Observations