Primary vs. Secondary data • Methods of collecting primary data (interviews, observation) • Questionnaires and schedules • Census vs. Sample surveys • Sampling techniques (Random, Stratified, Quota, Multistage

Here's a breakdown of the concepts you've listed:

• Primary vs. Secondary data

  • Primary data is original data collected directly by the researcher for the specific purpose of their study.
  • Secondary data is data that has already been collected by someone else for a different purpose and is available for use by the researcher.

• Methods of collecting primary data (interviews, observation)

  • Interviews involve direct verbal communication between a researcher and a respondent to gather in-depth information.
  • Observation is a method where researchers systematically watch and record behaviors, events, or characteristics in their natural setting without direct interaction.

• Questionnaires and schedules

  • A questionnaire is a set of written questions designed to gather information from respondents, typically self-administered by the respondent.
  • A schedule is similar to a questionnaire but is filled out by an enumerator or interviewer during a face-to-face interaction with the respondent.

• Census vs. Sample surveys

  • A census involves collecting data from every single unit or member of the entire population.
  • A sample survey involves collecting data from a subset (sample) of the population to make inferences or generalizations about the entire population.

• Sampling techniques (Random, Stratified, Quota, Multistage)

  • Random (Simple Random Sampling): Every unit in the population has an equal and independent chance of being selected for the sample.
  • Stratified Sampling: The population is divided into homogeneous subgroups (strata) based on certain characteristics, and then a random sample is drawn from each stratum.
  • Quota Sampling: A non-probability sampling method where researchers select participants based on pre-set quotas for specific characteristics (e.g., a certain number of men and women), but the selection within those quotas is not random.
  • Multistage Sampling: Involves selecting samples in stages, often starting with larger clusters or geographical units and then sampling smaller units within those selected clusters.