sampling

• What is the purpose of stratified sampling?

  To ensure that different subgroups of a population are represented in the sample.
• Why is stratified sampling considered time-consuming?

  Because it requires identifying and categorizing subgroups before sampling.
• What is volunteer sampling?

  It involves advertising for volunteers to participate in a study.
• What is a limitation of volunteer sampling?

  It may lead to a biased sample as only those who volunteer are included.
• What is snowball sampling?

  It is a method where existing study subjects recruit future subjects from among their acquaintances.
• Why might snowball sampling be difficult with skittles?

  Because it relies on personal connections rather than random selection.
• What are the steps to carry out random sampling?

  1. Define the target group.
  2. Determine the sample size.
  3. Assign numbers to each member of the population.
  4. Use a random number generator to select participants.
• What are the strengths of random sampling?

  It is easy to implement and free from bias.
• What is a limitation of random sampling?

  It can be time-consuming and difficult to ensure a truly random selection.
• What is opportunity sampling?

  • Involves asking members of the population of interest to participate.
  • Can lead to a biased sample.
  • May lack external validity as findings can't be generalized.
• What is stratified sampling and its advantages?

  • Involves dividing the population into subgroups (strata).
  • Reduces sampling bias.
  • Provides better generalizability.
  • Ensures representation of different segments of the population.
• What is systematic sampling?

  It involves selecting participants at regular intervals from a list of the population.
• How do you carry out systematic sampling?

  Define the population, assign numbers, choose a sample size, and select intervals.
• What are the strengths and weaknesses of snowball sampling?

  Strengths:

  • Cost-effective.
  • Useful for studying specialized populations.
  • Easy to understand and implement.

  
  

  Weaknesses:

  • Self-selection bias.
  • Low response rate.
  • Limited generalizability.
• What is qualitative data?

  Data that is descriptive and non-numerical.
• What is quantitative data?

  Data that is numerical and can be measured statistically.
• What are the strengths and weaknesses of qualitative and quantitative data?

  Strengths of qualitative data:

  • Provides in-depth insights.
  • Captures complex phenomena.

  
  

  Weaknesses of qualitative data:

  • Subjective and harder to analyze.
  • Limited generalizability.

  
  

  Strengths of quantitative data:

  • Objective and statistically analyzable.
  • Easier to replicate.

  
  

  Weaknesses of quantitative data:

  • May overlook context and depth.
  • Can be less flexible.
• What is the significance of having a representative sample?

  A representative sample allows for generalization of findings to the larger population.
• What are the consequences of using a non-representative sample in research?

  Findings cannot be generalized to the whole population.
• What is the definition of a target population?

  The group of people from which a sample is drawn for research.
• what are the different types of sampling?

  • random
  • opportunity
  • volunteer
  • systematic
  • stratified
  • snowball