1. 11 Chapter 6 The Research Process – Data collection & Data analysis – (Stage 5 & 6 in Research Process) © 2009 John Wiley & Sons Ltd. www.wileyeurope.com/college/sekaran

2.  Recall the Research process: 1)Broad problem area 2)Problem statement 3)Theoretical Framework 4)Generation of hypotheses 5)Data collection: 6)Data analysis: 7)Report Writing( Interpretation of results) 2 © 2009 John Wiley & Sons Ltd. www.wileyeurope.com/college/sekaran

3. Stage 5: Data collection  The process by which the researcher collects the information needed to answer the research problem.  In collecting the data, the researcher must decide: –Which data to collect –How to collect the data –Who will collect the data –When to collect the data 3 © 2009 John Wiley & Sons Ltd. www.wileyeurope.com/college/sekaran

4. Sources of Data  Primary data: information obtained first hand by the researcher on the variables of interest for the specific purpose of the study. Examples: Surveys, focus groups, panels, Questionnaires, Personal interviews.  Secondary data: information gathered from sources already existing. Examples: company records or archives, government publications, industry analyses offered by the media, web sites, the Internet, and so on. 4 © 2009 John Wiley & Sons Ltd. www.wileyeurope.com/college/sekaran

5. Ways of Searching for Suitable Data  Reading professional Journals; to learn what kind of data sources are being used, or how variables are formulated, measured or used by similar studies.  Reading books; it provides a description of various variables for the reader.  Talking with other researchers ; who may be familiar with specific tools or methods in their data collections.  Combining one or more tools; that are used by other researchers.  Developing your own method ; or approach to collect the data. 5 © 2009 John Wiley & Sons Ltd. www.wileyeurope.com/college/sekaran

6. Data Limitations  Most Data sources in empirical economic research papers are Secondary data.  When was it collected? For how long? –May be out of date for what you want to analyze. –May not have been collected long enough for detecting trends.  Is the data set complete? –There may be missing information on some observations 6 © 2009 John Wiley & Sons Ltd. www.wileyeurope.com/college/sekaran

7. Data Limitations  Are there confounding problems? –Sample selection bias? –Source choice bias? –In time series, did some observations drop out over time?  Are the data consistent/reliable? –Did variables drop out over time? –Did variables change in definition over time? 7 © 2009 John Wiley & Sons Ltd. www.wileyeurope.com/college/sekaran

8. Squeezing Data Limitations  Is the information exactly what you need? –In some cases, may have to use “proxy variables” – variables that may approximate something you really wanted to measure.  No need to reinvent the wheel. –If someone has already found the data, take advantage of it. 8 © 2009 John Wiley & Sons Ltd. www.wileyeurope.com/college/sekaran

9. Squeezing Data Limitations  Save your time by using your money. –Primary data collection is very time consuming. –Sometimes you have to pay for data access, thus it is cheaper in terms of money than collecting your own data.  Primary data has great exploratory value –Exploring research questions and formulating hypothesis to test. 9 © 2009 John Wiley & Sons Ltd. www.wileyeurope.com/college/sekaran

10. Data Collection Choice  What you must ask yourself? –Will the data answer my research question?  To answer that: –You must first decide what your research question is. –Then you need to decide what data/variables are needed to scientifically answer the question. 10 © 2009 John Wiley & Sons Ltd. www.wileyeurope.com/college/sekaran

11. Data Collection Choice  If that data exist in secondary data form, then use them to the extent you can, keeping in mind limitations.  But if it does not, and you are able to fund primary collection, then it is the method of choice. 11 © 2009 John Wiley & Sons Ltd. www.wileyeurope.com/college/sekaran

12. Stage 6: Data Analysis  Once data are ready for analysis, the researcher can test the hypotheses already developed for the study.  Data analysis and interpretation of results may be the most meaningfully explained by referring to business research project.  In this stage, the hypothesis will be tested using an statistical regression analysis. 12 © 2009 John Wiley & Sons Ltd. www.wileyeurope.com/college/sekaran

13.  The statistical system employs unique programming techniques to model the decisions that researchers make.  The researcher should learn how regression outputs are interpreted.  The data analysis should be based on testing hypotheses that have been already formulated.  BE AWARE!!! That It would be incorrect to change your original hypotheses to suit the results of data analyses. 13 © 2009 John Wiley & Sons Ltd. www.wileyeurope.com/college/sekaran

14.  However, it is acceptable to develop inductive hypotheses and later test them through further research.  In this stage, you should be able to summarize your results.  In addition, be ready to make recommendation based on your interpretation of the results. 14 © 2009 John Wiley & Sons Ltd. www.wileyeurope.com/college/sekaran