Applied statistics with SPSS
1
2022-2023
02022917
Statistics
Portuguese
Face-to-face
QUARTERIAL
2.0
Compulsory
Non Degree Course
Recommended Prerequisites
Not applicable.
Teaching Methods
Teaching takes place in theoretical-practical sessions in computer lab. In addition to classes, students will develop a computational project involving the statistical analysis of a real or simulated data set. This project, done individually or by a team of 2 students, includes the production of a written report and its discussion with the teacher.
Learning Outcomes
The main goal of this course is to update and complement the knowledge of students in applied statistics, preparing them to perform current statistical analysis supported by the software SPSS.
The main competencies to be developed are: understanding the fundamental principles underlying descriptive and inferential statistical reasoning; ability to perform current statistical analysis, selecting the most appropriate techniques and methods for collecting and processing statistical data; ability to use SPSS procedures in handling data files and performing statistical analysis, and to understand the outputs provided by the program; acquiring sensitivity and critical thinking towards arguments and conclusions based on statistical studies.
Work Placement(s)
NoSyllabus
1. Introduction to SPSS.
2. Exploratory analysis of quantitative and categorical data (univariate and bivariate samples).
3. Sampling techniques.
4. Statistical Inference.
4.1 Introduction: random variables and probability distributions; quantil-quantil plots.
4.2 Confidence intervals (CI) and parametric tests.
4.2.1 Basic concepts of interval estimation and hypothesis testing.
4.2.2 CI and tests for the mean of a gaussian population and for the difference between the mean of two gaussian populations (independent and paired samples); CI and tests for proportions.
4.3 Non-parametric tests: goodness of fit, Mann-Whitney, comparison of proportions; independence.
5. Linear regression model: definition and assumptions; inference for regression parameters; prediction; goodness of fit and diagnostic checking.
6. Analysis of variance: goals and terminology; one-way analysis; multiple comparison tests.
Assessment Methods
Assessment
Exam: 50.0%
the computational project : 50.0%
Bibliography
A. Field, Discovering Statistics Using SPSS, Sage Publications, 2005
B. Murteira, J. Ribeiro, C. Silva, C. Pimenta, Introdução à Estatística, 3ªed., Escolar Editora, 2010
D. S. Moore, G. P. McCabe, Introduction to the Practice of Statistics, 7ªed., Freeman and Company, 2011
D. Pestana, S. Velosa, Introdução à Probabilidade e à Estatística, 4ª ed., Fundação Calouste Gulbenkian, 2010
J. Maroco, Análise Estatística com utilização do SPSS, 5ªed., Pero Pinheiro, 2011
M. J. Norusis, SPSS 16.0 Guide to Data Analysis, Prentice-Hall, 2008