1. C M Clarke-Hill1 Collecting Quantitative Data Samples Surveys Pitfalls etc... Research Methods

2. C M Clarke-Hill2 Research Design Defining the Problem What Data is needed to solve it

3. C M Clarke-Hill3 Typical Stages Problem Definition Review of Secondary Sources Select Appropriate Approach for the Collection of New (Primary) Information Determine the Details of the Research Design Data Collection Analysis and Interpretation of the Data Evaluation and Recommendations

4. C M Clarke-Hill4 Data Types Secondary Data - Information that that is available from existing published sources –Internal to the Company –External to the Company Primary Data - Information has been collected for the first time –Can come from internal sources –External sources - survey data etc..

5. C M Clarke-Hill5 Data Sources Cont. Primary Data is usually collected by the means of: –A Survey –Depth Interviews –Observation of behaviour –Establishing Motivations –etc..

6. C M Clarke-Hill6 The Questionnaire and its Design The questionnaire is usually the common form of collection of survey data

7. C M Clarke-Hill7 Questions can either: Classify - organizations or people Describe Behaviour Discover Attitudes and Perceptions

8. C M Clarke-Hill8 Types of Questions Open Ended - Some sort of free form and expression on the part of the respondent Closed ( Structured) –Yes/No –Multiple Choice –Rankings –Check Lists

9. C M Clarke-Hill9 Wording the Questions Avoid Ambiguity Consider the Respondent’s ability to answer Consider the Respondent’s willingness to answer Avoid Influencing the Answer

10. C M Clarke-Hill10 Question Sequence Initial questions to provide motivation Logical order - general to the specific. This is known as funneling. Rotating the questions to reduce bias Difficult questions - where do you place theses in the questionnaire ? Routing and Excluding - be careful of the logic of your questionnaire.

11. C M Clarke-Hill11 Some Standard Questions Have you ever? Do you ever ? How Often ? When did you last ? Who does it ? In what way do you do it ? Which do you do more ? In the future will you ?

12. C M Clarke-Hill12 Some Points to Consider Is your questionnaire too long ? Do you need cards for your respondents ? Do you need to aid recall ? What is going to happen after the survey ? Avoid multi punch data - this leads to coding problems and data analysis problems How are you going to administer the survey?

13. C M Clarke-Hill13 Measuring Attitudes Attitudes influence preferences and are related to behaviour. They usually contain three components: –Beliefs –Emotions and –Behaviour

14. C M Clarke-Hill14 Measuring Attitudes Two Stages: –Pilot - some form of depth interview with a small group to ascertain the key characteristics –Survey to measure the attitudes and perceptions Use: –Adjective check lists –Multiple choice questions –Rating scales: Monopolar Vs Bipolar Scales, Likert Scales - 5 point or 7 point scales

15. C M Clarke-Hill15 Some Problems with Scales Are the chosen adjectives ambiguous ? Can meaning differ between respondents ? Scale length - short scales may not be sensitive enough, long scales may be unmanageable. What about the ‘don’t know’ Respondents often tend to choose the mid point.

16. C M Clarke-Hill16 How do you Reach your Respondent ? Mail Telephone Personal Interview All have different advantages and disadvantages for the researcher - Follow up to obtain a better response rate.

17. C M Clarke-Hill17 Sampling Why do we sample ? Types of Sample Issues about Samples

18. C M Clarke-Hill18 Basic Premise of Sampling The researcher is looking to generate data has is representative of the population from which the sample is drawn. Samples are practical as resources are finite Samples can give an accurate view of a phenomenon.

19. C M Clarke-Hill19 Sampling Process Decisions Who is to be surveyed ? The sampling unit. How many to be sampled ? The sample size. How can they be selected ? The sampling procedure.

20. C M Clarke-Hill20 Sampling Procedures Two broad categories: Probability Samples –Random - everyone in the population has an equal change of being chosen. –Stratified Random Sample - to account for a variable in the population –Sequential Sample –Cluster Sample

21. C M Clarke-Hill21 Sampling Procedures The opposite of Probability Samples is the Non Probability Sample: –Quota Samples –Judgmental Samples

22. C M Clarke-Hill22 Sampling Procedures In Selecting samples and sample size allow for non response. This can reduce the validity of your results Also be aware of bias in your survey. –Bias in non response –Bias by the interviewer –Bias through the questions asked –Sample bias –Bias from the respondents

23. C M Clarke-Hill23 Sample Frame Adequacy - in coverage of the population Completeness - missing units cannot be selected introducing bias No duplication - double counting Accuracy - is the sample frame up to date ? Convenience - Can the sample units be accessed at reasonable cost ?

24. C M Clarke-Hill24 Finally Editing –Has each relevant questions been answered ? –Accuracy - some inaccuracies can be spotted by eye. –Uniformity - have interviewers interpreted the questions and instructions in a uniform way ? Coding - think about your coding for data input Tabulating - think about your tables and cross tabulations. This is useful for the next stage on analysis