Question-Cum-Model-Solutions
Model Solutions
1. Discuss Questionnaire as a technique of data collection. What are the characteristics of a good questionnaire? 20
2. Explain the Probability Sampling strategies with examples. 10
Model Structure 1.
Introduction
● Define Questionnaire: Questionnaire is a set of printed or written questions with a choice of answers, devised for the purposes of a survey or statistical study. It is used primarily as a quantitative data collection tool.
Main Body
● Characteristics of a good questionnaire:
○ Unambiguous
○ It should not have doubtful questions
○ It should be appealing to the target audience
○ It should be brief
○ Aesthetically appealing
○ Mode of administration conducive to the target audience (soft/hard copy)
○ Coherent placement of questions
○ It should be intriguing
○ There shouldn’t be repetition
● Use of questionnaire in sociological research- explain with examples
○ Goldthorpe and Lockwood affluent worker study
● Advantages
○ Cheapest, fastest and relatively easiest method of quantitative data collection
○ High validity and reliability in close ended questionnaire
○ Flexibility in data collection
○ Highly objective
○ Limited need of experts
○ Scope for generalisation of data.
● Limitations of using questionnaire for data collection
○ Leading questions can influence the response of participant
○ Social desirability bias
○ Non-response bias
○ Poor return of postal questionnaire
○ Researchers bias → sequence and questions are decided by him/her based on own values Note: Advantages and Limitations can be eliminated or explained briefly in 10 marker question, but they must be explained in 20 marker question.
Conclusion
● Hybrid of quantitative methods like questionnaire and quantitative method must be used for sociological research.
○ Triangulation Method given by Norman K Denizen
○ Socio logic by Micheal Mann
Model Structure 2.
Introduction
● Definition of Sampling
● Definition of Probability Sampling
Main Body
● Types of Probability Sampling with slight explanation - simple random, stratified random, random cluster and systematic sampling (You can use figures for explaining these types)
● Examples - Use probability sampling to collect data, even if you collect it from a smaller population.
● Benefits - cost effective, simple and straightforward.
● Limitations - reliability of sample, problem of Quantification.
Steps to conduct probability sampling
- Choose your population of interest carefully and then include them in the sample.
- Determine a suitable sample frame
- Select your sample and start your survey
Conclusion
● Despite limitations, it provides cost effective and simple investigation of social issues.
