Experimental Planning and Data Analysis

Code:

CMRM112

Acronym:

CMRM112

Keywords
Classification	Keyword
OFICIAL	Marine Sciences

Instance: 2012/2013 - 1S

Active?	Yes
Responsible unit:	Instituto Português do Mar e da Atmosfera
Course/CS Responsible:	Master Degree in Marine Sciences - Marine Resources

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MCMRM	23	Specialisation in Marine Biology and Ecology 2008	1	-	2,5	25	67,5
		Specialisation in Aquaculture and Fisheries 2008	1	-	2,5	25	67,5

Teaching language

Suitable for English-speaking students

Objectives

It is intended that students acquire basic concepts inherent in the modern scientific method, including the identification of problems of scientific nature, the formulation of testable hypotheses to investigate and correct planning of data collection (experimental or sampling) permitting such research. On the practical, students are familiar with modern tools for effective manipulation and analysis of data, and some of the most commonly used statistical methods in the biological sciences.

Learning outcomes and competences

With the basic knowledge acquired in this course students should be able, independently, to plan the collection, manipulation and analysis of data for the investigation of simple problems. Should, above all, stay motivated for a future deepening of knowledge in the application of mathematical methods to biological problems.

Working method

Presencial

Program

1 - Brief Introduction to the R language

- Vectors
- Logical values
- Matrices
- Arrangements multidimensional data
- Dataframes
- Factors
- Data Import
- Some functions useful for data manipulation
- Creation of functions
- Optimization functions through vectorization calculations

2 - Planning sample

- Population, sample, sampling
- Simple random sampling
- Stratified random sampling

3 - Exploratory data analysis

- Summary Statistics
- Diagram of stem-and-leaf
- Histograms
- Graphics quantile-quantile
- Boxes mustaches
- Scatter plots x-y
- Graphics conditioned
- Variables correlated
- Variables confused
 
4 - probability distributions

- Probability
- Distribution of probabilities
- Normal Distribution
- Central Limit Theorem

5 - Hypothesis Testing

- The Student t test
- Error type I and type II, and power test
- The Student t test for two samples
- The Chi-square test
 
6 - Linear Models

- Method of least-squares
- Diagnostics adjustment
- Testing the parameters
- Analysis of variance and covariance

7 - Analysis Group

- Analysis of non-hierarchical groups
- Analysis of hierarchical groups

8 - discriminant analysis

Mandatory literature

Cadima, E.L., Caramelo, A.M., Afonso-Dias, M., Tandstad, M.O. ; Sampling Methods Applied to Fisheries Science: a manual., FAO. Roma., 2005
Dalgaard, P. ; Introductory Statistics with R, 2nd edition. , Springer. New York., 2008
Faraway, J.J. ; Linear models with R., Chapman Hall/CRC. Boca Raton., 2009
Kaufman, L., Rousseeuw, P.J. ; Finding Groups in Data: An Introduction to Cluster Analysis. , Wiley-InterScience. New Jersey., 2005

Complementary Bibliography

Sokal, R.R., Rohlf, F.J.; Introduction to Biostatistics 2nd Ed, Dover. New York., 2009
Chambers, J.M., Cleveland, W.S., Kleiner, B., Tukey, P.A. ; Graphical Methods for Data Analysis, Wadsworth & Brooks/Cole, 1983
Chen, C.H., Hardle, W., Unwin A. (eds.); Handbook of Data Visualization, Springer. Berlin., 2008
Cochran, W.G. ; 1977. Sampling Techniques 3rd ed. , John Wiley and Sons. New York.

Teaching methods and learning activities

Lectures and discussion.

Software

R

keywords

Physical sciences > Mathematics > Statistics
Social sciences > Educational sciences > Research methodology

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Description	Type	Time (hours)	Weight (%)	End date
Attendance (estimated)		110,00
Final exam	Exame	2,00	60,00
Assignment	Trabalho escrito	10,00	40,00
	Total:	-	100,00

Amount of time allocated to each course unit

Description	Type	Time (hours)	End date
	Frequência das aulas	25
Self study	Elaboração de projeto	43
	Total:	68,00

Calculation formula of final grade

Final rating = Rating at work (weight 40%) + Final Exam (60%)

Examinations or Special Assignments

Written exam with practical problem solving data analysis with R software and group work (groups with a maximum of 3 students) with an application of acquired knowledge to a data set obtained by the students.