Unit STATISTICS FOR BUSINESS
- Course
- International economics and management
- Study-unit Code
- 20A00063
- Location
- PERUGIA
- Curriculum
- In all curricula
- Teacher
- David Aristei
- Teachers
-
- David Aristei
- Hours
- 63 ore - David Aristei
- CFU
- 9
- Course Regulation
- Coorte 2022
- Offered
- 2022/23
- Learning activities
- Caratterizzante
- Area
- Statistico-matematico
- Academic discipline
- SECS-S/03
- Type of study-unit
- Obbligatorio (Required)
- Type of learning activities
- Attività formativa monodisciplinare
- Language of instruction
- Italian
- Contents
- The course is organized in five main parts:
1) Introduction to business statistics and data sources for business analysis
2) Survey methods and sampling techniques
3) Data analysis: measures of association
4) The linear regression model
5) Regression models for binary dependent variables - Reference texts
- Main textbook:
- Bracalente B., Cossignani M., Mulas A.: “Statistica Aziendale”, McGraw-Hill, Milano 2009.
Additional suggested textbook:
- Biggeri L., Bini M., Coli A., Grassini L., Maltagliati M.: “Statistica per le decisioni aziendali”, 2/Ed., Pearson, Milano 2017
Class slides and materials used during the laboratory sessions will be distributed through the UniStudium e-larning platoform - Educational objectives
- This course will introduce students to the most relevant statistical methods for business analysis.
In particular, theoretical lectures will be focused on the discussion of survey methods and sampling techniques and on the presentation of regression models for the analysis of economic and business data.
Specific attention will be also devoted to on empirical applications. Every week there will be a practical laboratory session in which students will apply concepts learned during the theoretical lectures, using the econometric software STATA. - Prerequisites
- This course requires basic knowledge of descriptive and inferential statistics and probability theory.
- Teaching methods
- Face-to-face lessons completed with practical laboratory activities
- Other information
- Attending students are to complete some (non-compulsory) take-home assignments
- Learning verification modality
- Written and oral examination
A non-compulsory intermediate written test will took place during the mid-term break - Extended program
- 1) Introduction to business statistics
Data sources for business analysis
2) Survey methods and sampling techniques
Probabilistic sampling techniques: simple random sampling, systematic sampling and stratified sampling
Estimating population mean and total
Types of surveys and data collection methods
3) Data analysis: measures of association
Association measures for qualitative and categorical data
Spearman's rank correlation coefficient
Pearson’s linear correlation coefficient
Inference of association measures
4) The linear regression model
Simple and multiple regression models
Parameters estimation by ordinary least squares
Goodness-of-fit
Hypothesis testing
Prediction
Diagnostic analyses: non-linearity, heteroscedasticity and multicollinearity issues
5) Regression models for binary dependent variables
The linear probability model
The logistic regression (logit) model
Estimation of logit parameters
Interpretation of results and inference
Predicted probabilities
Measures of goodness-of-fit