Probability and Statistics

Code:

M2013

Acronym:

M2013

Keywords
Classification	Keyword
OFICIAL	Mathematics

Instance: 2022/2023 - 1S

Active?	Yes
Responsible unit:	Department of Mathematics
Course/CS Responsible:	Bachelor in Agricultural Engineering

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
A:A	1	PE_Agronomia	1	-	6	56	162
L:EA	2	The study plan from 2019	2	-	6	56	162

Teaching language

Portuguese

Objectives

To show how statistical reasoning is used in sciences research and to enable students to perform simple statistical analyzes and to interpret the results. Particular attention is paid to the understanding of concepts and to the critical use of methods, while maintaining mathematical treatment at an elementary level.

Learning outcomes and competences

1. Be able to identify the techniques of descriptive statistics appropriate to organize and summarize a data set and to carry a basic data exploration using software R.

2. Dominate the fundamental concepts of probability calculus and know to calculate probabilities associated with the phenomenon under study.

3. Be able to characterize random variables and their probability distributions. Understand the characteristics and know how to apply the binomial and normal distributions in the modeling of processes.

4. Infer about the characteristics of a population based on a sample using point  and interval estimation.

5. Understand the general procedures and know how to select, apply and interpret hypothesis tests.

 

Working method

Presencial

Program

1. Brief introduction to the objectives and methodology of statistics.

2. Descriptive Statistics and exploratory data analysis: summarizing data (tables, graphs, measures of location and dispersion) using R.

3. Probability: basic concepts and properties, conditional probability and independence. 

4. Random variables: discrete and continuous, probability distributions, expected value and variance,  binomial and normal probability distributions, assessing normality.

5. Sampling distributions and central limit theorem.

6. Statistical inference:  interval estimation (mean, difference of means, proportion, difference of proportions), hypothesis testing:  t, chi-square, one-way ANOVA.

 

Mandatory literature

Samuels Myra L.; Statistics for the life sciences. ISBN: 978-0-13-122811-5 0-13-122811-0

Complementary Bibliography

Natália Cordeiro; Introdução à estatística. ISBN: 972-757-276-6
Douglas C. Montgomery; Applied statistics and probability for engineers. ISBN: 0-471-17027-5
Wild Christopher J.; Chance encounters. ISBN: 0-471-32936-3

Teaching methods and learning activities

The contents of the syllabus are mainly presented in the lectures, providing examples in order to illustrate and motivate the concepts and methods considered. Some specific  topics are only presented in the classes, where exercises and related problems are solved and discussed.

All resources are available for the students at the unit’s web page.

Software

R

keywords

Physical sciences > Mathematics > Statistics

Evaluation Type

Distributed evaluation without final exam

Assessment Components

designation	Weight (%)
Teste	100,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Estudo autónomo	106,00
Frequência das aulas	56,00
Total:	162,00

Eligibility for exams

Students must be present in one of the two assessments that are part of the evaluation.

Calculation formula of final grade

1. In the first call the final mark will be the sum of the scores obtained in two assessments: 

Assessment 1: with a total of 8 points, will take place in a date to be settled with students. 

Assessment 2: with a total of 12 points, will take place during the period settled for conclusion of distributed evaluation. 


2. In the second call, the final mark will be obtained in an exam with a total of 20 points. 
This exam will be divided in two parts, allowing the students which have not yet been aproved in the course (and only these students) to substitute the score in any of the two parts by the score obtained in the corresponding assessment. 

Special assessment (TE, DA, ...)

Students that, due to special conditions, are exempted from distributed assessment will have an exam under the conditions described for the second call.

Classification improvement

Improvement in the classification can be obtained in the second call only.