Fundamentals of Statistics

Code:

M1020

Acronym:

M1020

Level:

100

Keywords
Classification	Keyword
OFICIAL	Mathematics

Instance: 2018/2019 - 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	233	Official Study Plan	1	-	6	56	162
			3
L:F	1	Official Study Plan	2	-	6	56	162
L:G	0	study plan from 2017/18	3	-	6	56	162

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 the software R.

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

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), introduction to software 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 (randomization, 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

Wild Christopher J.; Chance encounters. ISBN: 0-471-32936-3
Montgomery Douglas C.; Applied statistics and probability for engineers. ISBN: 0-471-20454-4

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

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

The final exam will be divided into two parts.

The first of these parts may be held in a test taking place during the class time. Students who choose to take the test may also take both parts of the first season exam, thus annulating the test score.



In the second season exam (except in cases of improvement), students may use the 1st or 2nd part classifications obtained previously (in the test or in the first season exam).