Statistics

Code:

CINF052

Acronym:

E

Keywords
Classification	Keyword
OFICIAL	Mathematics

Instance: 2025/2026 - 1S

Active?	Yes
Web Page:	http://moodle.fe.up.pt
Responsible unit:	Department of Industrial Engineering and Management
Course/CS Responsible:	Bachelor of Arts in Information Science

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
CINF	46	Study plan	2	-	6	41	162

Teaching language

Portuguese

Objectives

SPECIFIC AIMS:
Provide students with an integrated view of Statistics and of its usefulness, making them capacitated users of Descriptive Statistics and Statistical Inference.

Learning outcomes and competences

LEARNING OUTCOMES:
At the end of the semester, the students should be able to:
- Explain and interpret the main statistical concepts;
- Use descriptive statistics tools to analyse sample or populational data;
- Solve common problems involving basic theory of probability, random variables, probability distributions, random sampling, confidence intervals and hypothesis testing.

Working method

Presencial

Program

1. Introduction to Statistics: Scope and method;
2. Descriptive statistics: Description of univariate and bivariate samples of quantitative or qualitative data:
3. Basic probability theory;
4. Random variables and probability distributions: distributions of discrete and continuous variables, distribution parameters transformed variables;
5. Joint distribution of two random variables: joint, marginal and conditional distributions, independent variables, covariance and correlation, distribution of functions of two variables.
6. Probability distributions of discrete random variables: the Binomial distribution, the Hypergeometric distribution and the Poisson distribution.
7. Probability distributions of continuous random variables: the Uniform distribution, the Negative exponential distribution, and the Normal distribution, the t distribution, the Chi-square distribution and the F distribution;
8. Random sampling and sampling distributions: distribution of the sample mean. the Central limit theorem, Generation of random smaples;
9. Statistical inference: confidence intervals;
10. Statistical inference: hypothesis testing.

Mandatory literature

Rui Campos Guimarães, José A. Sarsfield Cabral; Estatística. ISBN: 978-989-642-108-3
Wonnacott, Thomas H.; Introdução à estatística. ISBN: 85-216-0039-9

Teaching methods and learning activities

Theoric classes: presentation of the themes of the course illustrated by cases, examples and solving of illustrative problems.

Practical classes: clarify possible doubts about the proposed problems.

Software

Microsoft Excel

Evaluation Type

Evaluation with final exam

Assessment Components

Designation	Weight (%)
Exame	70,00
Trabalho prático ou de projeto	30,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	79,50
Frequência das aulas	42,00
Elaboração de projeto	40,50
Total:	162,00

Eligibility for exams

Students have to reach a minimum mark to be admitted to exams (See "General Evaluation Rules of FEUP - article 4).

Calculation formula of final grade

The final classification (CF) is obtained by the following formula:

CF = 0.7 E + 0.3 R

E: Exam.
R: Report

The Final Exam is credited for 75%.

Examinations or Special Assignments

There are no additional assignments.

Special assessment (TE, DA, ...)

Written Exam, weight 0.7, and project development, weight 0.3

Classification improvement

Global improvement: only by Exam, covering all the syllabus (weight: 0.75).