Quantitative Methods in Management Research (CMR50378)

General information

Type:	OB	Curs:	1	Period:	S semester
ECTS Credits:	3 ECTS

Teaching Staff:

Group	Teacher	Department	Language
	Joan M. Batista Foguet	Dirección de Personas y Organización	ENG

Basics of Calculus and of Matrix Algebra. Quantitative univariate and bivariate Methods, Exploratory Data Analysis, Basics of Probability, Sampling distributions, and Statistical inference: Estimation and Testing. Also a bit of common sense.

Statistics has nothing to do with a set of recipes to solve already specified problems. It is actually an instrument to help you to make decisions. My objective is that you learn THE CRAFT of statistics, the classical statistical methods and new trends on data analysis that the participants on the MRes are more likely to use in their future research.

I always try to focus mainly on core concepts and common sense before any statistical tool is provided, followed by presenting the advantages of the tool application and immediately the underlying assumptions and the usual flaws.

Upon completion of this course the participants will be able to:

- Use SPSS, to aid in managerial decision making based on knowledge of the variability and the interrelationships (dependence and interdependence) of the different aspects that could be of interest in a particular study
- Read literature on multivariate analysis as applied in the business world.
- Take advantage of the of the working group's heterogeneous backgrounds, of their different motivations and profiles for solving their own doubts and problems before asking for external help

11. Skillful in the use of quantitative methods

7. Ability to synthesise and generalise information

15. Ability to organise and plan

21. Interpersonal skills

17. Learn to participate in academic activities

6. Ability to reason analytically and reflectively

29. Focused on quality

27. Ability to work independently

1. Dependence Analysis of the relationships between continuous variables (Sessions 1st,2nd,3rd &¿ 4th) 1. Concepts already reviewed (Confidence Intervals, Hypothesis testing, significance test. Session ¿1st) 2. Sampling Covariance and Correlation coefficient 3. Rank correlation coefficient 4. Nominal & Continuous variables 5. Simple Linear Regression. A descriptive approach 6. Least squares adjustment criterion 7. Analysis of variation and goodness of fit 8. The Simple Linear Model. 9. Process of statistical modelling. Specification. Estimation. Testing. Prediction 10. Assumptions check. Residual analysis and influent data 11. Introduction to Multiple Regression. 12. Specification errors. Multicollinearity. ¿Building Regression Models. Usual algorithms¿. Dichotomous independent variables. Interaction (Moderate) effects.

2. Introduction to Multivariate Analysis (Session 4th) 1. Interdependency techniques. Classification, objectives and types of data. Examples. 2. Basics of measurement in marketing research. Real and measured phenomena. Dimensionality. Relevant information. 3. Representing data in Rp and RN.

3. Principal Components Analysis & Factor Analysis model (Sessions 5th& 6th) 1. Introduction to principal components analysis 2. Different definitions. Introductory concepts 3. A geometrical approach 4. Determining principal components: criteria and process 5. Correlation matrix analysis. Loadings 6. Analysing and interpreting results. Rotation 7. Factor Analysis Model 8. Introduction to the confirmatory approach

4. Simple Correspondence Analysis and HOMALS (Session 7th). 1. Introduction. Traditional analysis of qualitative data. Chi-square test. Weaknesses 2. Objective. Type of data. Notations. Practical applications of simple correspondence analysis (SCA). 3. Geometric approach to the study of relationships in a contingency table. Profiles and interdependence relationship. Centroid 4. Benzecri distance definition. Property of distributional equivalence 5. Adjustment criterion to obtain the factor structure. Concept of inertia 6. Factor interpretation. Absolute and relative contributions. The use of supplementary individuals 7. Introduction to Multiple Analysis of Correspondences and other related techniques.

5. Classification techniques. Cluster Analysis (Session 7th) 1. Objective 2. Prior decisions on the data matrix 3. Selecting similarity/dissimilarity measurements 4. Aggregation: criteria and process 5. Interpreting and analyzing results 6. Validating results: a feedback process

In order to show the relevance of the conceptual approach to statistics and to evaluate their diverse backgrounds there is Workshop 0, that should be done prior to the first session (in groups) which includes some (I assume) already reviewed concepts that we will discuss on the first session. In my experience most of the basic concepts are not understood in introductory or even in more advanced statistical courses.

The course begins by reminding you of Hypothesis testing and Significance tests. Then, the following seven sessions are split into two parts, in the first part the Simple Regression model is reviewed to introduce the Multiple Regression perspective.
The second part of the course is devoted to techniques of Multivariate Analysis as data reduction devices of the columns and rows of the original data matrix. That is, Factor Analysis, Correspondence Analysis and Cluster Analysis Techniques.

There are afternoon sessions to discuss and practice the concepts reviewed focusing, in particular, on the use of software packages and on the interpretation and validity of the results that are obtained from them.

During the sessions, participants will be provided with the material needed to follow this course. The material includes both the theoretical content of the different subjects to be discussed and practical exercises related to these subjects to be solved using SPSS.

Participants will be asked to read and to solve exercises outside the classroom, as well as, in the practical sessions, to discuss the content and the use of the various techniques in the light of the problems arising.

ASSESSMENT BREAKDOWN

Manuals-1. Albright, S.C., Winsten, W & Zappe, C.J. (2004). Data Analysis for Managers. Brooks/Cole (Sessions 1th through 4th).
2. Batista-Foguet, JM. & Martínez-Arias, MR (1989). Análisis Multivariante. Análisis en Componentes Principales. Hispano-Europea (If you are able to read Spanish) (Sessions 5th through 7th).
3. Batista-Foguet, JM.(1990). La prueba de significación: un procedimiento revalorizado. Editorial Signo (In Spanish). Free ítems available (Sessions 1th through 4th).
4. Batista-Foguet, JM. y Sureda, J. (1998). Análisis de Correspondencias. En J. Renóm Ed. Tratamiento informatizado de datos. Masson (In Spanish). Free ítems available (Sessions 5th through 7th).
5. Chatterjee, Samprit & Hadi, Ali S. (2006). Regression Analysis by Example. Wiley (Sessions 1th through 4th).
6. Gelman, A. & Hill, J. (2006). Data Analysis Using Regression and Multilevel/Hierarchical Models. Analytical Methods for Social Research. Cambridge University Press (Only, 2 to 4 chapters) (Sessions 1st through 4th)
7. Harnett, D.L. & Horrell, J.F. (1998). Data, Statistics and decision models with Excel. J. Wiley & Sons (Sessions 1th through 4th).
8. Mendoza, R. Batista-Foguet, J.M. & R. Oliva (1994). A. Life styles of European schoolchildren: findings of the WHO Cross National Study on Health-related Behaviour. En J.P. Dauwalder (Ed) Psychology and Promotion of Health. Hogrefe & Huber Publishers (Sessions 5th through 7th).
9. Lawrence C. Hamilton (1991). Regression with Graphics: A Second Course in Applied Statistics. Brooks/Cole (Sessions 1th through 4th).
Articles (with PhD Students)
1. Batista-Foguet, JM. Mendoza, R. Pérez, M & R. Rius (2000). Life-styles of Spanish school-aged children: their evolution over time. Use of Multiple Correspondence Analysis to Determine Overall Trends Over Time in a Sequential, Cross-Sectional Study. Advances in methodology, data analysis and statistics, Metodolo?ki zvezki, 16, 147-172. (Sessions 5th through 8th )
2. Batista-Foguet, JM., Fortiana, J., Currie, C. & J.R. Villalbi (2004). Socio-economic Indexes in Surveys for Comparisons between Countries. Social Indicators Research, V67. 315-332 (Sessions 5th through 7th).
3. Batista-Foguet, J.M., Coenders, G. & J. Alonso (2004). Análisis Factorial Confirmatorio. Su Utilidad en la Validación de Cuestionarios relacionados con la Salud. Medicina Clínica 122, 21-27(In Spanish; Sessions 5th through 7th)
4. Batista-Foguet, J.M.; Sipahi, A.; Guillén, L.; Martínez-Arias, MR. & Serlavós, R. (2016). Design and evaluation process of a personal and motive-based competencies questionnaire in Spanish-speaking contexts. The Spanish Journal of Psychology, 19, e14, 1-12. (Sessions 1st through 4th)
5. Batista-Foguet, J.M; Ferrer, B., Serlavos, R, Coenders, G. & Boyatzis, R. (2015). An alternative approach to analyze Ipsative data. Revisiting Experiential Learning Theory. Frontiers in Psychology, 6:1742. (Session 7th)
6. Bisbe, J. Batista-Foguet, J.M & Chenhall, R. (2007). Defining and measuring attributes of management control systems: a methodological note on the risks of conceptual misspecification. Accounting Organizations and Society, 32, (7-9), 789-820 (Sessions 5th through 7th)
7. Coenders, G., Casas, F., Batista-Foguet, JM. & González, M (2002). Living conditions, Interviewer effects and Perceived Well-Being of elderly. A Multiple Correspondence Analysis Approach. Developments in Social Science Methodology, Metodolo?ki Zvezki ,18, 125-146(Sessions 5th through 7th)
8. Folguera, C.; Fernández-Marín, X. & Batista-Foguet, JM. (2018). The Impact of Counselling, Training and Development on Absence of Employees with Disabilities. International Labour Review. 157, 4, 751-769
9. Loewe; N., Bagherzadeh; M., Araya-Castillo, L., Thieme, C. & Batista-Foguet, JM. (2015). Life Domain Satisfactions as Predictors of Overall Life Satisfaction Among Workers: Evidence from Chile. Social Indicators Research 118, 1, 71-86. (Sessions 5th through 7th)
10. Loewe, N.; M.; Araya, L.; Thieme Jara, C. & Batista-Foguet, J.M. (2014) Self-employment as a moderator of the relationship between work and life satisfaction. Academia Revista Latinoamericana de Administracion, 28, 2, 213 - 226
11. Mosteo, L.; Batista-Foguet, J.M.; McKeever, J. & Serlavós, R. (2015). Understanding Cognitive-Emotional Processing through a Coaching Process: The Influence of Coaching on Vision, Goal-directed Energy, and Resilience. Journal of Applied Behavioral Sciences (Sessions 1st through 4th)
12. Boyatzis, R.; Batista-Foguet, J.M; Fernandez-Marín, X. & Truninger, M. (2015). EI Competencies as a Related but Different Characteristic than Intelligence. Frontiers in Psy. 6: 72, 1-14 (Sessions 1st through 4th)
13. Murphy, M., Arenas, D. & Batista-Foguet, J.M. (2015) Value Creation in Cross-Sector Collaborations: The Roles of Experience and Alignment. Journal of Business Ethics, 130, 1, 145-162 (Sessions 1st through 4th)
14. Mendoza, R., Batista-Foguet, J. M., González, A. R., Baya, D. G., & Cruz, C. (2014). La lectura voluntaria de libros en el alumnado español de 10 a 18 años: diferencias territoriales, de género y características asociadas. Erebea. Revista de Humanidades y Ciencias Sociales, 4, 391-416.
15. Rufi, S., Javaloy, F., Batista-Foguet, J.M., Solanas, A. and Páez D. (2014). Flow Dimensions on Daily Activities with the Spanish Version of the Flow Scale (DFS). Spanish Journal of Psychology, 17, e30, 1-11(Sessions 5th through 7th)
16. Simões, CR., Batista Foguet, JM., Gaspar M. and Cameiro, L. (2008). Alcohol use and abuse in adolescence: Proposal of an alternative analysis. Child: Care, Health and Development, 34, 3, 291-30 (Sessions 5th through 7th)

Group	Teacher	Department
	Joan M. Batista Foguet	Dirección de Personas y Organización