Quantitative Methods

Code:

M114

Acronym:

MQ

Keywords
Classification	Keyword
OFICIAL	Medicine

Instance: 2024/2025 - 1S (of 16-09-2024 to 10-01-2025)

Active?	Yes
Responsible unit:	Population Studies
Course/CS Responsible:	Integrated Masters Degree in Medicine

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MIM	196	Official Study Plan	1	-	3	28	81

Teaching language

Portuguese

Objectives

The aim of this course is to familiarize first year students with basic statistical concepts and techniques essential for formulating and understanding models in biology.

Students should acquire skills to understand statistical principles and practical application of statistical models in biology. Skills in this case are of various orders, but basically it is intended that the student understand the usefulness of mathematical models for interpreting biological phenomena, as well as be able to realize, when you want to do a statistical study, what type of data to be collected, what type of analysis should be done in an attempt to obtain the desired results, i.e. the answer to research issues. The reality is that it is just that the student understand what role statistics play in the life Sciences. We do not intend to graduate the students as statisticians, but only someone who knows how to relate with statisticians

Learning outcomes and competences

The students at the end of the semester should be able to interpret scientific articles that make use of the techniques taught, as well as outline, analyze and interpret small basic statistical studies.

Working method

Presencial

Program

1. DESCRIPTIVE STATISTICS

Biological data and its graphical display; Probability and probability distributions.

1. STATISTICAL INFERENCE

Basic concepts of statistical inference: Sampling and sampling distributions; The Central Limit Theorem; Estimation and hypothesis testing; Confidence Intervals.

Inferences concerning means: Hypothesis testing and Confidence Intervals - Inference for a mean of a population; Comparing two means (paired and independent samples); The F test for comparing two standard deviations.

Inferences concerning proportions: Hypothesis testing and Confidence Intervals - Inference for a population proportion; Comparing two proportions (paired and independent samples); Comparing more than two proportions.

Correlation and Linear regression: The regression model. The method of least squares. Hypothesis testing and Confidence Interval for the regression slope. Correlation coeficient. Residual analysis.

Mandatory literature

Dawson-Saunders Beth; Basic and Clinical Biostatistics

Complementary Bibliography

Altman D. G.; Pratical Statistics for Medical Research, Chapman and Hall

Teaching methods and learning activities

The topics covered are introduced using an example of application in the biological sciences. The students will use SPSS software to solve complex exercises. Emphasis is given to teaching the need of understanding and using methods of formulating models, rather than the mechanical use of the techniques.

 

Software

IBM SPSS Statistics

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Teste	50,00
Trabalho prático ou de projeto	50,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	53,00
Frequência das aulas	28,00
Total:	81,00

Eligibility for exams

The evaluation will have two components:

Theoretical (T): In the practical lessons or by final examination.

Practical (P): In the last week of lessons (1st time students) or by final examination (for the remaining students).

Calculation formula of final grade

Formula Evaluation: 0.50xP + 0.50xT

The student must have at least 7 (out of 20) in each part.

Special assessment (TE, DA, ...)

The evaluation will have two components:

Theoretical (T) + Practical (P)

Final grade formula: 0.50xP + 0.50xT

The student must have at least 7 (out of 20) in each part.

Classification improvement

The evaluation will have two components:

Theoretical (T) + Practical (P)

Final grade formula: 0.50xP + 0.50xT

The student must have at least 7 (out of 20) in each part.