Biostatistics

Code:

CN11002

Acronym:

BIOEST

Keywords
Classification	Keyword
OFICIAL	Physical Sciences

Instance: 2020/2021 - 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	125	Plano oficial	1	-	3	42	81

Teaching language

Suitable for English-speaking students

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 have a notion of what is population and sample and 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 Pearson and Spearman correlation coefficients, the values of Cohen's k and odds ratio. They should be able to understand the concept of hypothesis testing and to interpret some common tests.
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.

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.

Aquisition of the notion of what is population and sample.

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 hypothesis testing).

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.

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

It is expected that the students have the following previous knowledge:
- Computation of descriptive statistic measures (namely frequencies, mean, median, mode and standard deviation).
- Classical definition of probability and combinatorics (combinations and partial permutatios with and without repetition).

Program

1 Random variable:
a) Notions of random variable, population and sample;
b) Simple random sampling;
c) 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 absolute frequency, relative frequency, cumulative absolute frequency, cumulative relative frequency, density of absolute frequency and density of relative density;
d) Graphical representation of data: stem and leaf diagram, box and extremes 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) Scatter plots, Pearson and Spearman correlation coefficients;
b) Crosstabs, agreement and Cohen's k and odds ratio;
c) Hypothesis testing - introduction;
d) Application examples of t-Student's test and of qui-square test for the independence.
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.

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	70,00
Participação presencial	0,00
Trabalho prático ou de projeto	30,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Estudo autónomo	21,00
Frequência das aulas	39,00
Trabalho de investigação	21,00
Total:	81,00

Eligibility for exams

To pass at this chair, he/she must obtain at least 8.0 points (out of 20) in the group work and in the written evaluation and a final grade of at least 9.5 (out ot 20).

In case of repetition of this chair, the final grade will be computed having in consideration their best grade, among this academic year and the two previous ones, regarding the group grade and regarding the participation grade.

Calculation formula of final grade

The evaluation of the participation, synchronous or assynchronous, of each student P, between -2 and 2, is computed in the following way:

P = sum(ai) / ns , where ns is the number of teaching weeks of the semester and ai is the evaluation of the participation between -2 and 2.


Students will do, along the semester, a group work that will be evaluated by an oral presentation in the end of the semester. The classifications G, betwen 0 and 20, have in consideration the following items:
- Dificulty of the statistical techniques (25%);
- Scientific correction (25%);
- Deepness and critical analysis in the Nutrition Sciences (25%);
- Presentation quality (25%).
To this classification it will be added an ammount, positive or negative, regarding the individual performance.
To be approved, the individual classification of the group work G will have to be greater than or equal to 8.0 out of 20.
This component will not be assessed in the Recourse Period.

Students that have obtained at least 8.0 (out of 20) in the individual classification of the group work may do the written evaluation E. This evaluation has to be above 8.0 out of 20 and may be obtained from the exam in the Normal Period or in the Recourse Period.


The quantity X, between 0 and 20, computed without the participation, is obtained by considering the written classification with weight 70% and the individual classification of the group work with weight 30%:
X = 0.7 * E + 0.3 * G.


In order to compute the bonus due to the participation, it is necessary to compute the proportion of the difference D betwen the quantity X and 20, a value between 0 and 1.

	{ (20 - X) / 10	if P>0  and  X>10
D =	{
	{ 1	if P≤0  or  X≤10

The final grade F, between 0 and 20, is computed in the following way:

	{ X + P * D	if E≥8.0 and  G≥8.0
F =	{
	{ min(E; G)	if E<8.0  or  G<8.0

Therefore, in case the participation has the maximum value of 2 points, the bonus shall correspond to a quantity between 0 and 2 (out of 20), proportional to D. In the event of a negative value of the participation, the final grade shall be less than the quantity X.

Special assessment (TE, DA, ...)

Students that are not enrolled in Methodologies for Food Consumption Assessment will have access to a database in order to do their group work.

Classification improvement

The improvement of classification will only focus on the classification of the final exam E, with 70% weight.

Observations

The support schedule will be defined and disclosed as soon as possible. To avoid periods of large affluence of students, we ask to schedule personally or by email up to the beginning of the afternoon of the previous weekday.

In the presential written evaluation, 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.

It will not be registered the absence to theoretical, theoretical-practical nor laboratorial practice classes.

According to the Rector Order GR.06 / 12/2017, Article 12, point e), students are not allowed to capture images or sound of the school activities.