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Questionnaire design and data preparation

Questionnaire design and data preparation. Class 7 Anjum P arvez. Objectives. Discuss the theoretical principles of questionnaire design Identify and explain the communication roles of questionnaire in the data collection process. Know how to eliminate common mistakes in questionnaire design

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Questionnaire design and data preparation

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  1. Questionnaire design and data preparation Class 7 AnjumParvez

  2. Objectives • Discuss the theoretical principles of questionnaire design • Identify and explain the communication roles of questionnaire in the data collection process. • Know how to eliminate common mistakes in questionnaire design • Understand the “Flowerpot” approach • Know how to eliminate common mistakes in cover letter design • Understand the 4-step approach to data preparation

  3. Questionnaires formal framework consisting of a set of questions/scales designed to generate primary raw data • Questionnaire construction

  4. Four Pillars of a Questionnaire Words Questions Hypotheses Formats

  5. Pillar 1 - Words Which to use in creating the questions and scales for collecting raw data from respondents • Wording Problems 1). Ambiguity 2). Abstraction 3). Connotation

  6. Pillar 2 - Questions Types of question formats: • Unstructured questions – open-ended, respondents reply in their own words • Structured questions – close-ended, responses to predetermined set of choices

  7. Pillar 2 – Questions (con’t) Question Quality - Good or bad? • Incomprehensible • Unanswerable • Leading or loaded • Double-barreled

  8. Pillar 3 - Hypotheses • designed for collecting meaningful raw data to test a hypotheses • Hypotheses relate to: 1). Nature of the respondent 2). Sociological structures and their influences on the respondent 3). Relationship between expressed attitudes and behavior of the respondent 4). Meaning of words and the respondent’s grasp of language and/or concepts 5). Descriptive and predictive capabilities of attributes of the constructs

  9. Pillar 4 - Formats The integrated layout of sets of question/scale measurements into a systematic instrument • Format should allow for clear communication

  10. “Flowerpot” Approach

  11. Discussion Question • Assuming you are conducting a study to determine the importance of brand names and features of mobile phones. What type of questions would you use? Open ended, closed ended, scaled? And why? Suggest 6-8 questions you would ask and in what sequence you would ask them?

  12. Cover Letters A separate written communication to a prospective respondent designed to enhance that person’s willingness to complete and return the survey in a timely manner

  13. Factors of Good Cover Letter Design 1. Personalization 2. Identification of the researcher’s organization 3. Statement of purpose 4. Anonymity and confidentiality 5. Time Frame 6. Reinforcement of the importance of participation 7. Acknowledge of reasons for not participating 8. Time requirements and compensation 9. Where to return 10. A thank you

  14. Ethical Considerations in Cover Letters According to Nipissing University’s Research Ethics Board, cover letters should include: • Identify the researcher and purpose • Description of procedures • Length of time required, frequency and location • Research findings availability • Potential risks and discomforts • Potential benefits to subjects and society • Compensation? • Confidentiality of data

  15. Discussion What are some of the advantages of developing good cover letters? What are some of the costs of a bad cover letter?

  16. Data Preparation 4-Step Approach 1. Data validation 2. Editing and coding of the data 3. Data entry 4. Data tabulation

  17. Step 1 - Data Validation To determine, to the extent possible, if the survey’s interviews or observations were conducted correctlyand free of interviewer fraud or bias Process of Validation • Fraud • Screening • Procedure • Completeness • Courtesy

  18. Step 2 – Editing and Coding Coding - grouping and assigning values • Codes are numerical • Designed into the questionnaire from the beginning • Master code must be established • For Open-end questions (4 steps) Editing- raw data are checked for mistakes Areas of Concern • Asking Proper Questions • Accurate Recording of Answers • Correct Screening Questions • Responses to Open-Ended Questions

  19. Step 3 – Data Entry Primary purpose of data entry – to ensure that the data entered are correct and error free Step in Error Detection • Review a printed representation • Produce a data/column list • Find the appropriate questionnaire

  20. Step 4 – Data Tabulation Two Common Forms of Data Tabulations • Simple one-way tabulation • Cross-tabulation

  21. One-Way Tabulations Purpose of technique: • To determine the degree of non-response to individual questions • To locate blunders of simple errors in the data entry • To calculate summary statistics on various questions

  22. Cross Tabulations • Primary form of data analysis in marketing research projects • Key elements - How to develop the cross-tabulation - How to interpret the outcome • Issues to Be Considered • Judgment of the analyst • Demographic lifestyle/psychographic variables • Technique is simple – hard to interpret

  23. Exercise • Keeping in mind the above mentioned discussion question; prepare a cover letter for the same purpose.

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