1. SylabUZ
2. Faculty of Exact and Natural Sciences
3. winter term 2020/2021
4. computer science and econometrics - Second-cycle studies leading to MS degree
5. Statystical Analysis in Market Research

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Statystical Analysis in Market Research - course description

Aim of the course

To familiarize students with fundamental methods used in statistical analysis of market data.

Prerequisites

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Passed lectures on: probability theory, descriptive and mathematical statistics.

Scope

Lecture

1. Marketing research. Measuring scales. Availability of data. (2 hours)
2. Methods of liner ordering of objects. (3 hours) 
   • The method of pattern development.
   • The method of standardized sums.
3. Introduction to classification methods. (4 hours)
   • The method of center of gravity.
   • Wroclaw taxonomy.
   • Decision (classification) tree.
4. Conjoint analysis. (3 hours)
5. Multivariate scaling. (3 hours)

   Laboratory

1. An introduction-repetition to chosen statistical package. (2 hours)
2. Partition, distinction and preliminary analysis of market data with respect to measuring scales. (2 hours)
3. Repetition with methods of analyzing market data with respect to measuring scales:
   1. methods used in descriptive statistics, (3 hours)
   2. statistical tests, (3 hours)
   3. analysis of relationships. (3 hours)
4. Test. (2 hours) 
5. Statistical methods with distinguish dependent variables. (5 hours)
6. Methods of
   1. classification of objects, (4 hours)
   2. linear ordering of objects, (2 hours)
   3. multivariate scaling. (2 hours)

      7. Test. (2 hours)

       

Teaching methods

Lecture - traditional. Laboratory – students analyze market data using properly chosen  procedures from statistical package.  

Learning outcomes and methods of theirs verification

Outcome description	Outcome symbols	Methods of verification	The class form

Assignment conditions

1. Laboratory – tests with tasks on different level of difficulty.
2. On the last lecture students refer statistical methods used in market research. Each student is graded. In the case of negative grade there is a possibility to get another date.

   To complete the course one has to obtain positive grades form laboratory and lecture. The course grade consists of a grade from lecture (30%) and a grade from laboratory (70%).

Recommended reading

Stanimir A. - pod red. "Analiza danych marketingowych Problemy, metody, zadania", Wydawnictwo Akademii Ekonomicznej im. Oskara Langego we Wrocławiu, Wrocław 2006

Mazurek-Łopacińska K. - pod red. "Badania marketingowe Teoria i praktyka", PWN Warszawa 2005

Walesiak M., Gatnar E. - pod red. "Statystyczna analiza danych z wykorzystaniem programu R", PWN Warszawa 2009

Maddala G.S. "Ekonometria", PWN Warszawa 2006

Aaker D.A., Kumar V., Day G.S. „Marketing Research”, John Wiley & Sons, Inc., New York, 1995.

Further reading

1. Biecek P. "Przewodnik po pakiecie R", Oficyna Wydawnicza GiS Wrocław 2011
2. Kopczewska K. ‘’Ekonometria i statystyka przestrzenna z wykorzystaniem programu R CRAN’’, Wydawnictwa Fachowe CeDeWu Warszawa 2006
3. Koronacki J., Ćwik J. "Statystyczne systemy uczące się", WNT Warszawa 2005
4. Welfe A. "Ekonometria Metody i ich zastosowanie", PWE Warszawa 1998
5. Welfe A. - pod red. "Ekonometria zbiór zadań", PWE Warszawa 1997
6. Dziechciarz J. - pod red. "Ekonometria Metody, przykłady, zadania", Wydawnictwo Akademii Ekonomicznej im. Oskara Langego we Wrocławiu Wrocław 2003
7. Zeliaś A. "Metody statystyczne", PWE Warszawa 2000
8. Zeliaś A., Pawełek B., Wanat S. "Metody statystyczne Zadania i sprawdziany", PWE Warszawa 2002

Notes

Modified by dr hab. Stefan Zontek, prof. UZ (last modification: 20-10-2020 11:48)