Week 1

1
Research Methods Data Analysis

• Week 1
• Introduction to the ModuleThe Research process

2
Research Methods Data Analysis

• Module convenor
• Dr. Mario Mazzocchi (M.Mazzocchi_at_reading.ac.uk)
• Room 310 Extension 6484
• Office hours Tue 2-4 Thu 11-1
• When and where Tuesday 11-1
• Room AG 1L06
• Web page www.personal.rdg.ac.uk/aes02mm/
• Mailing list

3
Web page
4
Intended outcome

• Have a first grasp of the market basic research
  techniques
• Become familiar with data analysis software such
  as SPSS or Excel
• Understand the (market) research process
• Acquire skills necessary to the group projects

5
Outline content

• The research design
• The survey plan and survey methods
• The Questionnaire and field work
• Sampling techniques
• Database management and preliminary data mining
  with SPSS
• Descriptive statistics and hypothesis testing
• Analysis of Variance
• Correlation and regression
• Research report preparation and presentation

6
Course plan
7
Textbooks

• There is no official textbook.
• These recent books can be especially helpful
• Fowler Jr., F.J (2002). Survey Research Methods,
  3rd Edition. Thousand Oaks CA Sage Publications.
• Survey basics Sampling basics Short and
  introductory
• Churchill, G.A., Iacobucci, D. (2002). Marketing
  Research Methodological Foundations. Harcourt
  College Publishers
• Complete manual many examples
• Malhotra, N.K. (1999) Marketing Research An
  Applied Orientation, 3rd Edition. Upper Saddle
  River (NJ) Prentice Hall.
• Complete manual very good for methodological
  reference

8
Module assessment

• Individual written assignment (70), answering to
  a specific research question, structured as a
  research report and covering the following
• Methodology
• Results
• Discussion
• Executive summary
• Examination (30) - One one hour examination
  paper (multiple choice test)

9
Coursework assignment

• The research question will be given on week 4 and
  will consist
• Of a marketing research problem
• Of a data-set to be analysed through one of the
  techniques discussed in the course
• The Lab sessions of 4 November and 2 December
  will be based on such data-set
• The short research report (max 1,200 words
  graphs / tables) should be delivered by the end
  of week 10

10
Lab Sessions

• Session 1 4 November
• Excel SPSS
• Basic descriptive statistics
• Graphs tables
• Session 2 2 December
• SPSS
• Hypothesis testing
• Analysis of Variance
• Correlation Regression

11
Exploratory vs. conclusive research

• Exploratory research
• Insights and understanding of the research
  problem
• Loose definition of information needed
• Flexible (unstructured) research process
• Small and nonrepresentative samples
• QUALITATIVE analysis of primary data
• Preliminary to further research

• Conclusive research
• Test specific hypothesis and examine
  relationships
• Clear definition of informational need
• Formal and structured research process
• Representative and large samples
• QUANTITATIVE data analysis
• Conclusive results for decision making

12
Primary vs Secondary data

• Primary data Data originated by a researcher for
  the specific purpose of addressing the problem at
  hand
• Secondary data Data collected for some purpose
  other than the problem at hand

13
A comparison of primary and secondary data
Source Malhotra, 1999
14
Qualitative research methods

• Qualitative research is a form of exploratory
  research which
• Provides an understanding of the problem and its
  underlying factors
• Is unstructured and flexible
• Based on small samples

15
Against

• QUALITATIVE RESEARCH
• Results cannot be uses as conclusive
• Results cannot be generalised to any population
• QUANTITATIVE RESEARCH
• Then thousand times nothing is still nothing

16
Situations where Qualitative R. is useful

• Impossible to use quantitative research (e.g.
  Developing Countries)
• People unable/unwilling to answer questions
• Need for emotional or affective information

17
The research process(with primary data)

• Formulate a research problem
• Determine the research design
• Design data-collection method and forms
• Design sample and collect data
• Analyse and interpret the data
• Prepare the research report

18
An example of research process

• A lecturer doesnt know the starting level of IT
  and statistical knowledge of its student and
  would like some extra information for better
  calibrating the module. Also, he would like to
  elicit students preferences about the
  mid-lecture break

19
1. The research problem

• Objectives
• Determine the general level of IT knowledge of
  the class
• Determine the level of statistical knowledge
• Determine the percentage of students that have
  used Excel or SPSS at least once
• Determine students preferences about the
  mid-lecture break

20
2. Determine the research design

• Exploratory research
• Conclusive research
• Informational need
• Sample
• Data collection
• Analysis (averages, percentages)
• Report

21
3. Design data-collection method and forms

• Primary data collection
• Questionnaire submitted in class before the break

22
The questionnaire
23
4. Design sample and collect data

• According to the student office, there should be
  44 students in this class
• There are 35 Students
• The sample is made by all students here today
• Possible selection bias
• Are characteristics of missing student related
  to IT/Statistical knowledge, preferences about
  the break?
• Please fill the questionnaire

24
5. Analyse and interpret the Data

• Data tabulation
• Summarised statistics
• Correlations allows to show the link between
  knowing statistics and having used SPSS or the
  link between knowing statistics and wanting no
  lecture at all.

25
Results

• On average you spend 2h 21min hours a day on a
  personal computer (standard error 2h 47min)
• 100 of you know at least one of the statistical
  terms of the questionnaire
• 77 know 3 or more of those terms
• 100 have used excel
• 2.8 have used SPSS
• The favoured option (74 of students) was
  Lectures should start at 11 and end at 12.40,
  with a ten minutes break

26
6. The research report

• Finally, a research report is provided. Results
  are summarised and conclusions are drawn.
• E.g. Student showed a good knowledge of IT tools,
  but SPSS needs to be explained from the
  foundations. Lectures should start at 11 and end
  at 12.40, with a ten minutes break
• The demand about having heard of statistical
  terms was not appropriate to infer the knowledge
  of statistics (as it emerged from preliminary
  qualitative research)

27
Some research problems related to food marketing

• Packaging of a food product (e.g. plastic or
  glass bottle for milk) - Product
• Communication to be given to consumers (e.g. beef
  after BSE scare) - Promotion
• Pricing for organic food - Price
• Development of on-line retailing - Place

28
Preparing a Research Proposal

• The Research Problem
• Purpose of the research project
• Data sources and methodology
• Time, personnel and costs

29
The Research Problem

• It is crucial to give a clear definition
• It is useful to identify its specific components
• How to define the problem
• Discussion with the decision maker (final user)
• Interview with experts in the topic
• Secondary analysis
• Qualitative research (e.g. Focus Groups)

30
Objectives the research questions

• They are detailed statements of the specific
  components of the problem
• Research questions depend on
• Problem definition
• Theoretical framework
• Analytical model adopted
• For conclusive research, it is very helpful to
  reach a further detail and formulate hypotheses,
  i.e. unproven statements about a factor or a
  phenomenon of interest

31
Data sources

• Explore available secondary data sources
• Primary data collection
• Exploratory research
• Qualitative research
• Survey plan
• Identification of the reference population
• Definition of the research questions
• Choice of sampling criteria
• Definition of the estimation methodology for
  making inference on the surveyed parameters
• Choice of sample size
• Choice of the data-collection method (method of
  administration)
• Questionnaire design
• Costs evaluation

32
Methodology of analysis

• Data preparation coding
• Cleaning and consistency checks
• Select a data analysis strategy
• Statistical techniques
• Univariate techniques
• Multivariate techniques

33
Univariate techniques
34
Multivariate techniques

• Cross-tabulation
• Correlation
• Analysis of variance
• Multiple regression
• Discriminant analysis
• Conjoint analysis
• Factor analysis
• Cluster analysis
• Multidimensional scaling

35
Time, personnel and costs

• Provide time estimates for each phase of the
  research
• Specify personnel required and their rates of pay
• Calculate nonpersonnel cost (such as printing,
  mailing)
• Travels

36
The Research Report

• Title page
• Table of contents
• Executive summary
• Introduction
• Results
• Conclusion
• Recommendations
• 4. Introduction
• 5. Body
• Methodology
• Results
• Limitations
• 6. Conclusions and recommendations
• 7. Appendix
• Questionnaire
• Sampling methodology and definition
• Other tables not in the report
• Bibliography

• Completeness
• Accuracy
• Clarity

37
The SPSS package

• Tutorials will provide a basic understanding of
  the software functioning
• An SPSS example will be given for most of the
  topics covered in this course. You are expected
  to be able
• To repeat the exercise
• To understand the SPSS output for each topic