Biostatistics

Code:

CN11002

Acronym:

BIOEST

Keywords
Classification	Keyword
OFICIAL	Physical Sciences

Instance: 2014/2015 - 1S

Active?	Yes
Course/CS Responsible:	Nutrition Sciences

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
CNUP	103	Plano oficial	1	-	3	42	81

Teaching language

Portuguese

Objectives

In the end of the semester, the students should be aware of the importance of the statistics in the scientific investigation. This chair has the objective of motivating the students to make an analysis of the statistical aspects of the studies they find or make.
To achieve that objective, the students should be able to distinguish different types of random variables.
In the analysis of data, the students should be able to compute the mean, median, mode, percentile, quartile, variance, standard deviation, skewness and kurtosis, both when the data is a statistical series or grouped in classes. The students should be able to present and understand data in tables and in graphs.
The students should be able to evaluate the relationship between pairs of variables, in particular, they should be able to interpret Cohen's k, odds ratio, Pearson and Spearman correlation coefficients and understand the concept of linear regression.
The students will need to make simple computations on probability, to distinguish independent events from exclusive events and to understand the definition of conditional probability. It will be important to know the difference between probability and odds. The students should also be able to interpret some probability functions, probability density functions and cumulative probability functions and they should be able to compute the expected value and the variance.
The students should have a notion of what is population and sample, to understand the importance of a random sample and should have a notion of what is a statistic and its sampling distribution.

Learning outcomes and competences

Awareness of the importance of the statistics in the scientific investigation.

Ability to make an analysis of the statistical aspects of studies.

Ability to distinguish different types of random variables.

Computation of means, medians, modes, percentiles, quartiles, variances, standard deviations, skewness and kurtosis.

Presentation and understanding of data in tables and in graphs.

Ability to evaluate the relationship between pairs of variables (interpretation of odds ratio, Cohen's k, Pearson and Spearman correlation coefficients and understanding the concept of linear regression).

Making simple computations on probability, distinguishing independent events from exclusive events, understanding the definition of conditional probability, and knowing the difference between probability and odds.

Interpretation of some probability functions, probability density functions and cumulative probability functions.

Computing the expected values and variances.

Aquisition of the notion of what is population and sample, understanding the importance of a random sample and aquisition of the notion of what is a statistic and its sampling distribution

Working method

Presencial

Program

1 Random variable:
a) Notion of random variable;
b) Scales of measurement of random variables: nominal, ordinal, interval, ratio, discrete and continuous.
2 Descriptive statistics:
a) Statistical series and grouped data;
b) Conversion of statistical series in grouped data – Sturges' formula;
c) Tables of frequency, relative frequency, cumulative frequency, cumulative relative frequency, density and relative density;
d) Graphical representation of data: Stem and Leaf diagram, box and whiskers diagram, bar chart, histogram, frequency polygons and density polygons;
e) Localization parameters: Mean, Median, Mode, Quartile and Percentile;
f) Dispersion and shape parameters: variance (with Sheppard's correction), standard deviation, dispersion coefficient, skewness and kurtosis.
3 Relation between pairs of variables:
a) Crosstabs, odds ratio, agreement and Cohen's kappa;
b) Scatter plots, Pearson and Spearman correlation coefficients;
c) Linear regression.
4 Probability theory:
a) Axiomatic definition of probability;
b) Independent, complementary, exclusive and mutually exclusive events;
c) Conditional probability;
d) Total Probability Theorem and Bayes' Theorem.
e) Notion of probability function, probability density function and cumulative distribution function;
f) Expected value and variance of a random variable;
5 Study of samples:
a) Notions of population and sample;
b) The relevance of sampling, random sampling;
c) Notion of statistic and sampling distribution.

Mandatory literature

Daniel Wayne W.; Biostatistics. ISBN: 0-471-16386-4
Guimarães Rui Campos; Estatística. ISBN: 972-8298-45-5

Complementary Bibliography

Clegg Frances; Estatística para todos. ISBN: 972-662-411-8

Teaching methods and learning activities

Theoretic classes (1h00/week): expository and interrogative method.
Theoretical-practice classes (1h00/week): interrogative and demonstrative method, with the resolution of exercises.
Laboratory classes (1h00/week): interrogative and demonstrative method, with the resolution of exercises in a computer.

Software

SPSS
Excel
R

keywords

Physical sciences > Mathematics > Statistics > Medical statistics
Physical sciences > Mathematics > Statistics

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Exame	90,00
Participação presencial	10,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	39,00
Frequência das aulas	42,00
Total:	81,00

Eligibility for exams

For a student (in the ordinary regimen) to be eligible for exam at Bioestatistics, he/she must not have more than the legal limit of missed classes (without proper justification) nor he/she may have a practical classes grade below 9.5 points (out of 20). To pass at this chair, he/she must obtain at least 8.0 points (out of 20) in the written exam and a final grade of at least 9.5 points (out of 20).

Each student will have a practical classes grade according to his/her participation on classes and his/her assiduity to the classes. This practical classes grade have a 10% weight in the final grade.

Students eligible for the Biostatistics exams in one of the two previous academic years can be dispensed from classes. Their final grade will be computed having in consideration their best practical classes grade in this academic year and the two previous ones.

Calculation formula of final grade

The final grade is computed in the following way:

F = 0.9 x E + 0.1 x P, where E represents the written exam grade and P the practical classes grade.

For the students with practical class grade above 9.5 (out of 20), it will be given a bonus of 0.001 x P² to their final grade, having the final grade a maximum of 20 (out of 20).

 

In the written exam, the answers must be written in blue or black ink in the given sheets. It will not be allowed the use of corrective (white) ink. Scientific calculators will be allowed, provided they have not the ability of plotting graphs and are not programmable. Furthermore, it will not be allowed the use of equipment with the ability of remote communication.

Special assessment (TE, DA, ...)

Students may request, until the end of October, excuse fromattending the classes (TP and PL). For the students that were excused, the final grade will only be the written exam grade .

Observations

The support schedule for Biostatistics will be:

Tue. 13h00 to 15h00;

Fri. 11h00 to 12h30.
 

The support schedule during the examination weeks will be 7h before the exam of the Normal epoch and 7h before the exam of the Recourse epoch. The exact date and time will be announced after the exams calendar will be available and may be consulted inside the Biostatistics' Document.