Applied Statistics II

Code:

C208

Acronym:

EST II

Keywords
Classification	Keyword
OFICIAL	Statistics

Instance: 2011/2012 - 1S

Active?	Yes
Web Page:	https://sigarra.up.pt/fdup/disciplinas_geral.formview?p_ano_lectivo=2010/2011&p_cad_codigo=C208&p_periodo=1S
Course/CS Responsible:	Criminology

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
C	78	Oficial Study Plan LC	2	-	6	-

Teaching language

Portuguese

Objectives

This course complements the statistical background initiated with Applied Statistics I. Specifically, we want that students in the end of this course:
1. Be able to conduct a quantitative exploratory analysis of data in order to explain criminal phenomena
2. Dominate the use of statistical techniques in social sciences and specifically in criminology.
3. Be able to explore quantitative associations between studied variables and to identify causality relationships.
4. Be able to work with statistical software packages (specially SPSS software)

Program

1) Review of important concepts studied in previous course “Applied Statistics I”

1.A) Data preparation for analysis
1.A.1. Preliminary analysis of data
1.A.2. Exploring main assumptions (normality and homogeneity of variances)
1.A.3. Correcting data problem
1.A.4. Data preparation on PASW (SPSS)

2) Relationship between variables
2.1. Categorical variables
2.1.1. Chi-square distribution
2.1.2. The one-variable goodness of fit Chi-square test
2.1.3. Contingency tables and the two-variable chi-square test of independence
2.1.4. Measures of association (between categorical variables)
2.1.5. PASW examples

2.2. Non-categorial variables
2.2.1. Pearson linear correlation coefficient
2.2.2. Spearman correlation coefficient
2.2.3. PASW examples

2.3. Simple linear regression models
2.3.1. Introduction
2.3.2. Simple linear regression
2.3.3. Simple linear regression and correlation
2.3.4. Interpreting simple regression
2.3.5. PASW examples

2.4. Multiple regression models
2.4.1. Introduction
2.4.2. Simple linear regression
2.4.3. Interpreting simple regression
2.4.4. PASW examples

3) Diferences between two groups

3.1. Independent groups (samples)
3.1.1. T-test for independent samples
3.1.2. Mann-Whitney U Test
3.1.3. PASW examples

3.2. Dependent (matched) groups (samples)
3.2.1. Related sample t test
3.2.2. Wilcoxon

4) Diferences between more than two groups
4.1. Independent groups (samples)
4.2. Dependent groups (samples)

5) Applied Statistics II complements
5.1. Logistic regression
5.2. Principal Component Analysis
5.3. Factorial Analysis
5.4) Meta-analysis

Mandatory literature

Bachman Ronet; Statistical for criminology and criminal justice. ISBN: 978-0-07-312924-2
Weisburd David; Statistics in criminal justice. ISBN: 978-0-387-34112-5
Marôco, João; Análise estatística com o PASW Statistics (ex-SPSS). ISBN: 9789899676305

Complementary Bibliography

Bachman Ronet; The^practice of research in criminology and criminal justice. ISBN: 978-1-4129-5032-9
Bushway Shawn 340; Quantitative methods in criminology. ISBN: 0-7546-2446-3
Pestana Maria Helena; Análise de dados para ciências sociais. ISBN: 972-618-297-2
Howell, david; statistical methods for psychology. ISBN: 0495012874

Teaching methods and learning activities

Two types of classes: Theoretical and Laboratorial applied work
Theoretical concepts are presented and explained in theoretical classes. Afterwards, those concepts are applied in laboratorial work, trying to prepare students to be able to make their own research on criminology.

Software

Software de folhas de cálculo (e.g., Excel)
IBM SPSS v. 19

keywords

Physical sciences > Mathematics > Statistics
Social sciences > Criminology

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Description	Type	Time (hours)	Weight (%)	End date
Attendance (estimated)	Participação presencial	65,00
Final Exam	Exame	2,50
	Total:	-	0,00

Eligibility for exams

In order to complete with success the course on Applied Statistics II, students must attend an written final exam (EF) and complete an (practical) written assignment (T), with a final weighted sum of at least ten points.

Calculation formula of final grade

Final classification = 0,65xEF + 0,35xT, where EF e T.
EF and T are classified individually in a range between zero and twenty points.

Examinations or Special Assignments

See previous note.

Special assessment (TE, DA, ...)

According to Main Regulation of the University and of the Criminology course.

Classification improvement

According to Regulations of the University and of the Criminology course.
In order to improve grades in this course, student must repeat a written final exam and/or written assignment.