STATISTICS 1
STATISTICA 1
A.Y. | Credits |
---|---|
2017/2018 | 6 |
Lecturer | Office hours for students | |
---|---|---|
Fabio Bordignon | Every week both in the active and in the passive semester. Contact the Lecturer via e-mail. |
Assigned to the Degree Course
Date | Time | Classroom / Location |
---|
Date | Time | Classroom / Location |
---|
Learning Objectives
The main aim of the course is to introduce the logic and the basic concepts of statistics, with particular attention to the applications in the fields of economics and business administration. Specifically, the course focuses on univariate and bivariate descriptive statistics, but it also provides an introduction to time series analysis and to inferential statistics. The applications regard real data, the presentation and discussion of results.
Program
I Introduction to Statistics
- Statistics: definitions
- Statistics in the framework of empirical research
- The operationalisation of concepts
- From properties to variables, from the units of analysis to cases
- The data matrix
- Types of variables
- Statistical data and data collection
- Official statistics
II Univariate analysis
- Frequency distribution
- Measures of central tendency
- Measures of variability
- Robust measures of central tendency and variability
- Concentration
- The shape of a distribution (symmetry, kurtosis and normal distribution)
- Graphical representation
III Introduction to time series
- Simple and multiple time series
- Fixed base index numbers
- Chain base index numbers
- Rate of annual change
- Composite index numbers
- The components of a time series
IV Bivariate analysis
- Measures of relationship between two variables
- Contingency tables
- Relationships between quantitative variables
V Regression
- Exploration, description, explanation
- The regression model
- Linear regression
- The ordinary least square method
- Total variation, explained variation, residual variation
- Coefficient of determination
- Interpolation in the case of time series
VI Introduction to inferential statistics and statistical sampling
Bridging Courses
Mathematics
Learning Achievements (Dublin Descriptors)
- Knowledge and understanding: at the end of the course students must have acquired the knowledge of the basic concepts of statistics, with particular reference to the techniques of univariate and bivariate analysis. Educational methods used to reach these goals: frontal lectures, exercises, class discussion.
- Applying knowledge and understanding: the students must be able to identify and apply appropriately, to real research and analysis situations, the concepts, the techniques presented throughout the course. In particular, they must be able to apply the acquired knowledge in the fields of economics and business administration. Educational methods used to reach these goals: frontal lectures, exercises, class discussion.
- Making judgements: the students must be able to link concepts presented throughout the course, to deal with complex problems independently, to make judgements and critical reflections. Educational methods used to reach these goals: exercises and class discussion.
- Communication skills: the students must be able to clearly and incisively communicate, appropriately using the lexicon of statistics. Educational methods used to reach these goals: exercises and class discussion.
- Learning skills: the students must develop adequate learning skills, so as to be able to extend and deepen the knowledge acquired throughout the course, following new paths of research and analysis and acquiring new knowledge. Educational methods used to reach these goals: frontal lectures, exercises, class discussion.
Teaching Material
The teaching material prepared by the lecturer in addition to recommended textbooks (such as for instance slides, lecture notes, exercises, bibliography) and communications from the lecturer specific to the course can be found inside the Moodle platform › blended.uniurb.it
Teaching, Attendance, Course Books and Assessment
- Teaching
Frontal lectures with slides, exercises, class discussion
- Course books
Testi di studio consigliati:
- Milioli M.A., Riani M., Zani S. (2015), Introduzione all'analisi dei dati statistici. Terza edizione ampliata, Pitagora Editrice, Bologna
The chapters attending students need to study will be specified during the course. Additional teaching material and exercises could be made available by the lecturer during the course via the Moodle platform > blended.uniurb.it.
Additional book for exercises:
- Cerioli A., Milioli M.A., Riani M. (2012), Esercizi di statistica, Uni.Nova
- Assessment
Written exam following the standard exams calendar:
- 1 theoretical question regarding the chapters covered during the course and the additional teaching material and exercises made available via the Moodle platform;
- 3 exercises.
The time for completing the exam will be 1,5 hours. More specific information about the exam will be provided via the Moodle platform.
- Disability and Specific Learning Disorders (SLD)
Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.
To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.
Additional Information for Non-Attending Students
- Course books
- Milioli M.A., Riani M., Zani S. (2015), Introduzione all'analisi dei dati statistici. Terza edizione ampliata, Pitagora Editrice, Bologna
- Cerioli A., Milioli M.A., Riani M. (2012), Esercizi di statistica, Uni.Nova
Non-attending students are not supposed to study the additional teaching material and exercises made available by the lecturer during the course via the Moodle platform > blended.uniurb.it.
- Assessment
Written exam following the standard exams calendar:
- 1 theoretical question regarding all the chapters of the textbook;
- 3 exercises.
The time for completing the exam will be 1,5 hours. More specific information about the exam will be provided via the Moodle platform.
- Disability and Specific Learning Disorders (SLD)
Students who have registered their disability certification or SLD certification with the Inclusion and Right to Study Office can request to use conceptual maps (for keywords) during exams.
To this end, it is necessary to send the maps, two weeks before the exam date, to the course instructor, who will verify their compliance with the university guidelines and may request modifications.
Notes
The student can request to sit the final exam in English with an alternative bibliography.
« back | Last update: 31/07/2017 |