- Docente: Silvia Pacei
- Credits: 6
- SSD: SECS-S/03
- Language: English
- Teaching Mode: Traditional lectures
- Campus: Bologna
- Corso: Second cycle degree programme (LM) in Statistics, Economics and Business (cod. 8876)
Learning outcomes
At the end of the course the student has a wide knowledge of the different typologies of official and non-official, and conventional and non-conventional sources of data that can be useful to the company, and has the ability to match the available data sources to the information needs of the company. The student possesses the knowledge of the tools to design and implement a new survey, in order to obtain useful information for the company, taking into account the peculiarities of this type of information and the consequent aspects that characterize its analysis. Moreover, the student knows the problems related to non-sampling errors and is able to deal with them using modern correction techniques. The student is able to implement all the practical tasks using a statistical software. In particular the student is able to: - decide the most suitable source of information for a specific information need of the company; - plan and carry out a sample survey; - organize the data obtained and correct them by using a statistical software.
Course contents
1. Sources of data for business. Official and non-official, conventional and non-conventional data sources.
2. Sample surveys. Sampling error. Probability sampling and alternatives. Complex probability sampling used in consumer and firm surveys.
3. Panel and rotating panel surveys. Choice of the sample dimension. How to calculate and correct sampling weights.
4. Sources of errors in surveys. The “non-response” and its consequences. Types of non-response: a) errors in the list; b) total non-response; c) item non-response.
5. Types of error in the lists and methods to control for them.
6. Total non-response. Reasons for total non-response. Consequenses of total non-response. How to prevent total non-responses or correct them during the survey. Total non-response correct in the estimation phase. Role of auxiliary variables.
7. Item non-response. Typologies of item non-response. How to prevent the item non-responses. Methods to deal with incomplete data: Weighting Methods and Imputation Methods. Comparative Analysis among imputation methods. Multiple Imputation.
SAS PROGRAMMING ON REAL OR SIMULATED DATASET.
Readings/Bibliography
Slides.
S.L. Lohr (2010). Sampling: Design and Analysis, Second Edition, Brooks / Cole, Boston. Teaching methods.
Carl-Erik Särndal, Sixten Lundström (2005). Estimation in Surveys with Nonresponse, John Wiley & Sons.
Teaching methods
Lectures and laboratory exercises using the SAS software.
As concerns the teaching methods of this course unit, all students must attend Module 1, 2 [https://www.unibo.it/en/services-and-opportunities/health-and-assistance/health-and-safety/online-course-on-health-and-safety-in-study-and-internship-areas] on Health and Safety online.
Assessment methods
Laboratory exam with eligibility, preparatory to the oral exam with a mark, to be taken in the same exam call.
The exam is aimed at verifying: the level of understanding and in-depth analysis of the topics, the ability to perform the relative logical-deductive connections, the knowledge of the basic vocabulary.
Office hours
See the website of Silvia Pacei