INRS Sampling and Qualitative Data Collection Methods

What is random sampling in research?

• Random sampling in research is a method where only a few select individuals are chosen to participate.

• Random sampling in research involves selecting participants based on their personal preferences.

• Random sampling in research means choosing participants based on their availability.

• Each member of the population has an equal chance of being selected to participate in the study.

What is an example of purposive sampling?

• An example of purposive sampling is choosing participants based on their favorite color.

• Purposive sampling involves randomly selecting participants for a study.

• Selecting participants for a study on the impact of social media usage on teenagers' mental health by specifically choosing teenagers who are heavy users of social media platforms.

• Purposive sampling is only used in qualitative research.

Explain how snowball sampling works in data collection.

• Starting with a small group of participants who then refer others to participate in the study, leading to an expanding sample size.

• Snowball sampling requires the researcher to collect data only from a single source.

• Snowball sampling involves randomly selecting participants from a population.

• Snowball sampling is a method where participants are chosen based on their demographic characteristics.

What are focus groups and how are they used in research?

• Focus groups are used in research to analyze quantitative data

• Focus groups are used in research to gather insights, opinions, and perceptions on a specific topic by bringing together a small group of people under the guidance of a moderator.

• Focus groups are used in research to observe animal behavior

• Focus groups are used in research to conduct surveys online

Describe the process of conducting interviews in qualitative research.

• Select participants, design questions, conduct interviews, transcribe responses, analyze data, draw conclusions.

• Design questions, analyze responses, draw conclusions

• Select participants, analyze data, draw conclusions

• Conduct interviews, analyze data, draw conclusions

How are observations used as a data collection method?

• By systematically recording information about behaviors, events, or characteristics of interest in a structured and objective manner.

• By guessing randomly without any structure

• By asking leading questions to influence responses

• By ignoring any data collected and making assumptions

Differentiate between semi-structured interviews and structured interviews.

• Structured interviews are more time-consuming than semi-structured interviews.

• Semi-structured interviews have a fixed question order, while structured interviews allow for flexibility.

• Semi-structured interviews have flexibility in question order and wording, while structured interviews follow a fixed set of standardized questions.

• Structured interviews allow for open-ended questions, while semi-structured interviews use closed-ended questions.

What are open-ended interview questions and why are they important?

• Open-ended questions are irrelevant in interviews

• Closed-ended questions are better for interviews

• Open-ended questions limit candidate responses

• Open-ended interview questions are important because they encourage detailed responses and provide insights into candidates' skills and personality.

What is probability sampling and when is it used?

• Probability sampling is used when researchers want a biased sample.

• Probability sampling is used when researchers want to exclude certain groups from the sample.

• Probability sampling is used when researchers want a representative sample and need to make statistical inferences about the population.

• Probability sampling is used when researchers want to make guesses without statistical backing.

Identify the advantages and disadvantages of non-probability sampling.

• Systematic sampling, unbiased results

• Convenience sampling, high generalizability

• Advantages: convenient, cost-effective; Disadvantages: potential bias, limited generalizability

• Random sampling, representative sample