Statistics

Code:

114

Acronym:

114

Instance: 2021/2022 - 2S

Active?	Yes
Course/CS Responsible:	Sports Sciences

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
LCD	271	First Degree in Sports Sciences (2011/2012)	1	-	5	45	135

Teaching language

Portuguese

Objectives

The UC Applied Statistics, in the 1st year of Sport Sciences studies, aims to fullfil a fundamental purpose - to allow students a wise use of quantitativa data obtained in the most varied contexts - school and sports field.
In this UC, knowledge is based on fundamental topics of Descriptive and Inferential Statistics as a function of the number of available classes.

Learning outcomes and competences

1. To understan and integrate the importance of Statistics in Sport Sciences research.
2. To know how formulate substantive questions and translate them in Statistical terms.
3. To know how to compute and interpret different kinds of data (univariate and bivariate) from Descriptive Statistics procedures.
4. To know how formulate hypothesis in Statistical terms, test them and adequately interpret the results.
5. To deal, with some degree of autonomy, SPSS and Excel softwares, to know basic commands of main statistical procedures and interpret the output.
6. To know how to extract main information from SPSS and Excel outputs, do manual calculations about the main issues explained in class and try to link them in a scientific document.

Working method

Presencial

Program

α1. Applied Statistics for 1st year students - main aims, classes structure, assessments and supprt material. A broad view of all topics will be presented. Measurement scales and data analysis. The need of data organization - series, relative and absolute frequencies. Graphical representations.
2. Data aggregated in classes. Relative and absolute frequencies, as well as graphical representations. data description based on central tendency measures - mode, median and mean. Which one to chose?
3. Numerical data description- Variation measures (range, variance and standard deviation). Sum of sqaures. Standard deviation interpretation as well as effect size. Measures of order - quantiles. Box-plot diagram and interpretation.
4. Normal distribution. Introduction and its importance. z distribution. z and t scores. Problem solving.
5. Simple linear correlation. Graphs and the idea of covariance. How to compute r and interpretation. Assumptions. Introdution to the idea of simple linear regression. Coefficnt interpretation. Precision and prediction. Interpretation of r2.
6. Probability distributions and sampling. Central limit theorem. Uses of z statistic and introduction to the idea of probability calculations. Sample size.
7. Hypothesis testing. Null and alternative hypothesis. z test, level of significance and p-values.
8. tests for differences between means. Sampling distribution of difference between means. T distribution and problem solving. w2 interpretation and effect size.
9. Test for mean differences based on sampling distributions. Computations of t statistic as well as % ALT. Problem solving.
10. test for hypothesis with 3 or more groups. ANOVA I. F test. A posteriori tests. Problem solving.
11. Non-parametric statistics based on exaples. Chi-square, Wilcoxon and Mann-Whitney tests.

Mandatory literature

Vincent William J.; Statistics in kinesiology. ISBN: 0-7360-0148-4
Pestana MH, Gageiro JN; Análise de Dados para Ciências Sociais. A Complementaridade do SPSS, Edições Sílabo
Minimum EW, Clarke RC, Coladarci T; Elements of Statistical Reasoning, John Wiley & Sons, Inc

Teaching methods and learning activities

Main lectures.
Practical classes with several Statistical procedures done by hand and also by SPSS and Excel softwares.
Discussion groups.

Evaluation Type

Evaluation with final exam

Assessment Components

designation	Weight (%)
Exame	70,00
Trabalho laboratorial	30,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Estudo autónomo	90,00
Frequência das aulas	45,00
Total:	135,00

Eligibility for exams

In order to access to the final exam all students should fulfll the following criteria:
i) be present in at least 75% of all theoretical and practical classes
ii) positive assessment in all demands of the practical classes

Those students who do not meet the criterium of, at least 75% of all theoretical and practical classes (workers and high level athletes) should contact the head of this UC within 15 days after the first class so that an anternative path will be set for them always within artigo 8, ponto 2, Diário da República, 2ª Série – nº 93 – 15 de maio de 2014.

Calculation formula of final grade

The final exam has 70% and the practical classes 30% of the final mark (NF). The NF is calculated according to the following formula:
NF=(7*(mark of the final exam)+2*(mark of practical classes)+0.5*(assiduity)+0.5*(interest))/10.

Special assessment (TE, DA, ...)

Students not present in 75% of all theoretical and practical classes (workers, and high level athletes) should contact the head of this UCwithin 15 days after the first class so that an anternative path will be set for them.

Classification improvement

Those who want to better their mark should proceed according to available  legislation. Any student who wants to better his/her final mark has the support from all teachers in order to optimize his/her knowledge, especially in those topics where they have more difficulties.