Statistics

Code:

L.EGI014

Acronym:

EST

Keywords
Classification	Keyword
OFICIAL	Statistic and Operational Research

Instance: 2021/2022 - 1S

Active?	Yes
Responsible unit:	Department of Industrial Engineering and Management
Course/CS Responsible:	Bachelor in Industrial Engineering and Management

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
L.EGI	101	Syllabus	2	-	6	52	162

Teaching language

Portuguese

Objectives

TThis course unit aims to acquaint students with underlying knowledge on Descriptive Statistics, Probability
Theory, Probability Distributions, Random Sampling, Sampling Distribution, Point and Interval Estimates, and
Statistical Inference. At the end of the curricular unit, students should be able to use the methods and techniques of
statistical analysis critically and with autonomy in the preparation of decisions. At the end of the study cycle, students are expected to have a global view of the concepts, problems, and tools available so that they can apply the techniques of multivariate statistics within the scope of Industrial management.

Learning outcomes and competences

At the end of the semester, students should be capable of:

• identifying the concepts of this course unit in a structured way;
• using descriptive statistics tools in the analysis of data samples;
• solving common problems, which involve elementary probability theory, random variables, probability distributions, point and interval estimation andstatistical hypothesis testing (parametric and nonparametric);
• using spreadsheets to solve the above mentioned problems.

Working method

Presencial

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

Basic spreadsheets skills.

Program

• Introduction to Statistics. Statistical Method.
• Descriptive Statistics. Summarizing Data.
• Spreadsheet Engineering. Data Organization and Visualization in Spreadsheets.
• Probabilities. Conditional Probability. Bayes Theorem.
• Random Variables. Probability Distributions. Population Parameters. Joint Probability Distributions. Transformed
Variables.
• Main Discrete and Continuous Distributions.
• Sampling and Random Sampling. Sampling Distributions. Central Limit Theorem. Generation of Random Samples with
Spreadsheets.
• Estimators and Estimates. Desirable Properties. Estimation Methods.
• Confidence Intervals. Confidence Intervals for Expected Values, Variances and Proportions. Sample Size
Determination.
• Introduction to Statistical Inference. Hypothesis Testing Methodology. Main tests for Expected Values, Variances and
Proportions. Relationship between Hypothesis Testing and Confidence Intervals.
• Introduction to Non-parametric Inference.

Mandatory literature

A. Miguel Gomes, Armando Leitão e José F. Oliveira; Estatística - Apontamentos de Apoio às Aulas, 2019
Guimarães, R. M. C. e J. A. Sarsfield Cabral; Estatística, Verlag Dashöfer Portugal, 2010. ISBN: 978-989-642-108-3

Complementary Bibliography

Nathan Tintle, Beth L. Chance, George W. Cobb, Allan J. Rossman, Soma Roy, Todd Swanson, Jill VanderStoep; Introduction to Statistical Investigations, Wiley, 2015. ISBN: 978-1-119-15430-3
Jay L. Devore, Kenneth N. Berk; Modern mathematical statistics with applications. ISBN: 978-1-4614-0390-6
Thomas Wonnacott, Ronald J. Wonnacott; Introdução à estatística. ISBN: 85-216-0039-9

Teaching methods and learning activities

Methods and techniques are introduced using systematically practical examples. The learning process is complemented with problem solving sessions supported by computer software and at least one teamwork assignment.

Software

Folhas de Cálculo

keywords

Physical sciences > Mathematics > Statistics
Physical sciences > Mathematics > Probability theory

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Exame	65,00
Teste	20,00
Trabalho prático ou de projeto	15,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Elaboração de projeto
Elaboração de relatório/dissertação/tese
Estudo autónomo	110,00
Frequência das aulas	52,00
Total:	162,00

Eligibility for exams

Admission criteria set according to Article 4 of General Evaluation Rules of FEUP.

Calculation formula of final grade

The final mark (CF) will be obtained by the following formula:
CF = 0.20 TI + 0.15 TG + 0.65 EF

TI - Intermediate test

TG - Teamwork assignments:


EF - Final Exam
- written exam.

To pass this course, apart from a final grade no less than 10, is required a minimum grade of 7 in the final exam.