Statistics I

Year
1
Academic year
2019-2020
Code
01007868
Subject Area
Methodology
Language of Instruction
Portuguese
Mode of Delivery
Face-to-face
Duration
SEMESTRIAL
ECTS Credits
6.0
Type
Compulsory
Level
1st Cycle Studies

Recommended Prerequisites

Secondary education subjects: Mathematics A, B, or Applied Mathematics to Social Sciences (MACS).

Teaching Methods

 Lecturing is mostly used for teaching the syllabus contents in the theoretical classes.

Demonstrating and collaboration methods will be mainly use in the lab classes.

Learning Outcomes

The curricular unit of Statistics I focuses on the development of statistical thinking (e.g., concepts, reasoning), persistence (leading to the use of knowledge and statistical skills after completion of discipline), and attitudes and beliefs (about value and the importance of statistics and about oneself as apprentices and users of Statistics) of future psychology scientist-practitioners. It also seeks to promote the development of practical skills in data analysis, in particular, using computer reference tools. For example, using the IBM SPSS Statistics for Windows program, students will be able to create a data file, manipulate and create variables, produce various types of graphs, and use a series of elementary statistical inference procedures (parametric and non-parametric tests applied to frequencies, means, variances and other types of statistics).

Work Placement(s)

No

Syllabus

A - Theoretical concepts

1. Introduction: The basic language of statistics

2. Elements of measurement

3. Descriptive statistics and exploratory data analysis (EDA)

4. Location measures (other than central tendency measures) and transformation of scores

5. Introduction to probability (elementary) and the Normal distribution

6. Inferential statistics: Point and interval estimation and the question of statistical significance (the logic of Null Hypothesis Significance Testing: NHST)

7. Parametric tests procedures envolving sample means: t-test procedures for one and two samples (independent and related)

8. Non parametric tests for one and two samples

9. Analysing categorical data (frequencies): the chi-square test.

B - Labororatory

1. Introduction of the IBM SPSS Statistics

2. The study of variables via several SPSS menus (e.g., Data, Transform, Analyze, and Graphs)

Head Lecturer(s)

José Manuel Tomás Silva

Assessment Methods

Assessment
Frequency: 100.0%

Bibliography

Cohen, B. (2008). Explaining Psychological Statistics. Hoboken, NJ: Wiley.

 

Field, A. (2017). Discovering Statistics Using IBM SPSS (5th ed.). London: SAGE.

 

Glass, G. V. & Hopkins, K. D. (1996). Statistical Methods in Education and Psychology (3rd ed.). Boston: Allyn & Bacon.

 

Guéguen, N. (1999). Manual de estatística para psicólogos. Lisboa: CLIMEPSI.

 

Howell, D. (1997). Statistical methods for psychology (4ª Ed.). Belmont, CA: Duxbury Press.

 

Marôco, J. (2018). Análise Estatística com o SPSS Statistics (7ª ed.). ReportNumber: Pêro Pinheiro.

 

Norusis, M. (2012). IBM SPSS Statistics 19 Guide to Data Analysis. Upper Saddle River, NJ: Pearson.

 

Pallant, J. (2016). SPSS Survival Manual: A Step by Step Guide to Data Analysis Using IBM SPSS (6th ed.). London: Open University Press.

 

Pestana, M. H. e Gageiro, J. N. (2014). Análise de Dados para Ciências Sociais - A complementaridade do SPSS (6ª ed.). Lisboa: Sílabo..