Quantitative Methods
A.Y. 2018/2019
Learning objectives
Undefined
Expected learning outcomes
Undefined
Lesson period: Second trimester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
Second trimester
ATTENDING STUDENTS
NON-ATTENDING STUDENTS
Module 1
Course syllabus
Collection, preparation and quality control of data
Review of Iinference and Bivariate Analysis
- Sampling, probability and Inference
- Correlation and regression
- Association
- Conforted medium
SPSS software will be used
Review of Iinference and Bivariate Analysis
- Sampling, probability and Inference
- Correlation and regression
- Association
- Conforted medium
SPSS software will be used
Module 2
Course syllabus
Multiple linear regression
Models for categorical response variables
Factor analysis and principal components analysis
Correspondence analysis
Cluster analysis
Case study
SPSS software will be used
Models for categorical response variables
Factor analysis and principal components analysis
Correspondence analysis
Cluster analysis
Case study
SPSS software will be used
Module 1
Course syllabus
Collection, preparation and quality control of data
Review of Iinference and Bivariate Analysis
- Sampling, probability and Inference
- Correlation and regression
- Association
- Conforted medium
SPSS software will be used
Review of Iinference and Bivariate Analysis
- Sampling, probability and Inference
- Correlation and regression
- Association
- Conforted medium
SPSS software will be used
Module 2
Course syllabus
Multiple linear regression
Models for categorical response variables
Factor analysis and principal components analysis
Correspondence analysis
Cluster analysis
Case study
SPSS software will be used
Models for categorical response variables
Factor analysis and principal components analysis
Correspondence analysis
Cluster analysis
Case study
SPSS software will be used
Module 1
SECS-S/01 - STATISTICS - University credits: 6
Lessons: 40 hours
Professor:
Salini Silvia
Module 2
SECS-S/03 - ECONOMIC STATISTICS - University credits: 6
Lessons: 40 hours
Professor:
Leorato Samantha
Professor(s)
Reception:
Next office hours: Thursday 17.04 online only (send an email to request an appointment); Thursday 24.04 from 9:30 to 12:30, online only (send an email to request an appointment); Tuesday 29.04 from 10:30 to 12, Wednesday 30.04 from 14 to 15:30
Room 32 third floor
Reception:
The student reception on Thesday from 10.00 to 13.00 in presence of via Teams (is better to agree an appointment) - Next Tuesday's student reception will not be held due to other academic commitments. Please contact the professor for another appointment.
DEMM, room 30, 3° floor or in Teams