20149 - QUANTITATIVE METHODS FOR MANAGEMENT
Department of Decision Sciences
REBECCA GRAZIANI
Mission & Content Summary
MISSION
CONTENT SUMMARY
The course focuses on multivariate statistical techniques widely used in business analytics. Through the course students are taught how to set up the appropriate analysis, implement it through the use of a statistical software (SPSS) and give an interpretation to the obtained results. The following techniques are discussed in detail
- Multiple linear regression
- Logistic regressions
- Factor analysis
- Cluster analysis
Intended Learning Outcomes (ILO)
KNOWLEDGE AND UNDERSTANDING
- Read reports and scientific articles that make use of basic and advanced statistical techniques.
- Set up and run empirical analyses, that require the use of basic and advanced statistical techniques.
APPLYING KNOWLEDGE AND UNDERSTANDING
- Use a statistical software (SPSS) to run multivariate statistical analyses to support management decision making.
- Contribute to the commissioning and interpretation of reports of business research, including market research and program evaluations.
Teaching methods
- Face-to-face lectures
- Online lectures
- Exercises (exercises, database, software etc.)
- Individual assignments
- Group assignments
DETAILS
Exercises are delivered as Tests through Bboard platform for E-Learning as in-class simulation of the exams. They are multiple choice questions and essay questions, with solutions provided as Feedbacks.
Assignments are delivered through Bboard platform for E-Learning as takehome. Students are asked to run analyses of provided datasets with short reports to be posted through Bboard platform for E-Learning. An evaluation grid is provided as well.
Group assignments. Students are asked to analyse a provided dataset and write a report with the interpretation of the analyses, to be posted through Bboard platform for E-Learning. The evaluation grid as for the individual assignments is used.
Assessment methods
Continuous assessment | Partial exams | General exam | |
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ATTENDING AND NOT ATTENDING STUDENTS
Two partial exams or a general general, four take-homes and a final assignment
Partial Exams and General Exam
The two partial exams are delivered asTests through Blackboard platform for E-Learning. The tests include both multiple choice questions and essay questions.
The general exam is delivered as Test through Blackboard platform for E-Learning. The test includes both multiple choice questions and essay questions.
Students answer the questions based on the theory and/or the inspection of SPSS outputs. Partial tests and general test are graded out of 31. The arithmetic average of the partial tests marks or the general exam mark contribute by 50% to the final grade.
The tests aim at assessing the students acquired knowledge on the content of the course, in particular with reference to the first and fourth Intended Learning Outcomes, as the ability to read reports and scientific articles that make use of basic and advanced statistical techniques and to contribute to the commissioning and interpretation of reports of business research, including market research and programme evaluations.
Take-homes
Delivered at the end of each Block of lectures through Blackboard platform for E-Learning. Students are asked to run with SPSS the analysis of a provided dataset so to apply the techniques learnt in the corresponding Block. A brief report with the description of the results and comments needs to be posted in Blackboard platform for E-learning, according to the schedule below.
The Take-homes let build piece by piece the skills related to the second and the third Intended Learning Outcomes, as to set up and run empirical analyses, that require the use of basic and advanced statistical techniques and the use a statistical software (SPSS) to run multivariate statistical analyses to support management decision making.
Takehome | Delivery date | Due date (by midnight) |
1 | 9/13 | 9/30 |
2 | 10/4 | 10/11 |
3 | 11/15 | 11/22 |
4 | 11/29 | 12/6 |
The take-homes can be made individually or in group of at most 5 students. Groups do not need to be the same.
The arithmetic average of the take-home marks contributes by 10% to the final grade. A take-home that is not handed in is marked 0.
Final Assignment
The assignment consists in an analysis of a provided dataset based on a research question, set by the instructor. The assignment is delivered on 3rd of December 2021. The report with a description of the results and comments needs to be posted in Blackboard platform for E-Learning by the 23rd of December 2021. The results are going to available by the 10th of January 2022.
Students who are registered for the exam scheduled on the 20th of December 2021 and want to know the assignment's mark before, need to post the assignment by the 12th of December 2021. In this case, the mark is going to be communicated on the day of exam, before its start.
The final assignment can be made individually or in group of at most 5 students. 1 point is awarded if the assignment is done in group.
The final assignment is graded out of 31 and contributes 40% to the final mark.
Both the evaluation grid of the take-homes and the general exam is provided.
The Final Assignment achieves the second and the third Intended Learning Outcomes, as the ability to set up and run empirical analyses, that require the use of basic and advanced statistical techniques
and the use a statistical software (SPSS) to run multivariate statistical analyses to support management decision making.
Teaching materials
ATTENDING AND NOT ATTENDING STUDENTS
- R. GRAZIANI, E. GREGORI, Lectures notes on Multivariate Statistical Analyses with SPSS, delivered through Bboard platform for E-Learning.
- Video Lectures and Slides delivered through Bboard platform for E-Learning.
- Additional Readings: TARLING, ROGER, Statistical Modelling for Social Researchers. Principles and practice, London and New York, Routledge, 2009. Bartholomew, D.J., Steele, F., Moustaki, I., Galbraith J.I. 2008. Analysis of Multivariate Social Science Data (second edition). Chapman & Hall/CRC, Warner, R.M. 2012. Applied Statistics. Sage