Fundamentals of Statistics

Code:

M1020

Acronym:

M1020

Level:

100

Keywords
Classification	Keyword
OFICIAL	Mathematics

Instance: 2019/2020 - 2S

Active?	Yes
Web Page:	https://moodle.up.pt/course/view.php?id=347
Responsible unit:	Department of Mathematics
Course/CS Responsible:	Bachelor in Biology

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
L:B	235	Official Study Plan	1	-	6	56	162
			3
L:EG	8	The study plan from 2019	2	-	6	56	162
L:F	2	Official Study Plan	2	-	6	56	162
L:G	3	study plan from 2017/18	2	-	6	56	162
			3

Teaching language

Portuguese

Objectives

To show how statistical reasoning is used in life 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 Excel.

2. Understand basic and fundamental concepts of probability and statistical inference with emphasis on applications to biology.

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 biological 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

À distância

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 Excel.

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-tests for mean and difference of means, chi-square tests of goodness of fit, independence and homogeneity).

 

Mandatory literature

Samuels Myra L.; Statistics for the life sciences. ISBN: 978-0-13-122811-5 0-13-122811-0
Pedrosa, António & Gama, Sílvio ; Introdução Computacional à Probabilidade e Estatística com Excel, Porto Editora, 2016. ISBN: 978-972-0-01990-5

Complementary Bibliography

Wild Christopher J.; Chance encounters. ISBN: 0-471-32936-3
W. W. Daniel & C. L. Cross; Biostatistics, a Foundation for Analysis in the Health Sciences, Wiley, 2013. ISBN: 978-1-118-30279-8

Teaching methods and learning activities

Until  16th March:
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.


From 16 March:
(distance learning due to the covid epidemic19)
On  MoodleUP, creation of a section dedicated to each week of work, which includes
a. Explanatory videos of the syllabus;
b. Document with the work plan for that week with a clear indication of the theoretical subject to be studied (indication of the videos to be viewed and the slides with the subject covered) and exercises to be performed;
c. Other material related to the topic to be studied that can facilitate the study, such as detailed resolution of some exercises.


Detailed resolution of exercises or detailed clarification of doubts posed by students through the forum available on Moodle.
Weekly communication using the Colibri / Zoom tool within the scheduled times for TP classes where students' doubts are clarified.

Software

Excel

keywords

Physical sciences > Mathematics > Statistics

Evaluation Type

Evaluation with final exam

Assessment Components

designation	Weight (%)
Exame	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

Without restrictions.

Calculation formula of final grade

Exam's score if less than or equal to 17. If the exam's score is greater than or equal to 17.5, a complementary assessment, oral or written, may be required, to take place in a date to fix with the students. In this case, the final grade can be 17, 18, 19 or 20 values and will only depend on on the student's performance in this complementary assessment.

Observations

Jury:
Helena Mena Matos
Teresa Mendonça