5.5.1 Sampling Techniques

    Cards (46)

    • What is the purpose of sampling in population studies?
      Draw conclusions about the population
    • Sampling offers several benefits, including reduced costs and time
    • The formula for estimating population density, DD, is D = \frac{\text{Number of individuals \in sample}}{\text{Area of sample plot}}</latex>.
    • Which sampling technique is ideal for uniformly distributed populations?
      Random sampling
    • Systematic sampling is suitable for large areas with consistent distribution
    • When is stratified sampling used in population studies?
      When the population is divided into subgroups
    • Random sampling ensures an unbiased selection because every individual has an equal chance of being chosen.
    • Systematic sampling can introduce bias if intervals coincide with population patterns
    • What is a weakness of stratified sampling?
      It requires detailed knowledge of subgroups
    • Steps involved in random sampling
      1️⃣ Identify the population
      2️⃣ Assign numbers to each individual
      3️⃣ Select numbers randomly
      4️⃣ Collect the sample
    • Random sampling minimizes selection bias, providing a true representation of the population.
    • What is the primary benefit of sampling in population studies?
      Reduces costs and time
    • Match the sampling technique with its strength:
      Random Sampling ↔️ Ensures unbiased selection
      Systematic Sampling ↔️ Good for large, consistent areas
      Stratified Sampling ↔️ Ensures representation of subgroups
    • Why is random sampling considered unbiased?
      Every member has equal chance
    • A large sample size is essential in random sampling to ensure representativeness.
    • What is the defining characteristic of stratified sampling?
      Dividing population into subgroups
    • One advantage of stratified sampling is that it ensures each stratum contributes proportionally
    • Stratified sampling reduces sampling error in heterogeneous populations compared to random sampling.
    • What does stratified sampling ensure in terms of subgroups within a sample?
      Proportional contribution
    • Stratified sampling involves dividing the population into subgroups based on shared characteristics
    • Stratified sampling reduces sampling error in heterogeneous populations.
    • What is the formula for calculating sample size in proportional allocation for stratified sampling?
      n_{i} = N_{i} \times \frac{n}{N}</latex>
    • Match the step in systematic sampling with its description:
      Define Population ↔️ Identify the entire group
      Calculate Sampling Interval ↔️ K=K =Nn \frac{N}{n}
      Choose Random Start ↔️ Select a number between 1 and K
      Select Sample ↔️ Choose every Kth individual
    • One advantage of systematic sampling is its simplicity
    • What is the primary purpose of sampling in population studies?
      Efficient estimation
    • Sampling reduces costs by measuring fewer individuals.
    • The formula for estimating population density is D=D = \frac{\text{Number of individuals \in sample}}{\text{Area of sample plot}}, where D represents density
    • Match the sampling technique with its strength:
      Random Sampling ↔️ Ensures unbiased selection
      Systematic Sampling ↔️ Simple and uniform selection
      Stratified Sampling ↔️ Ensures representative samples
    • Which formula is used for proportional allocation in stratified sampling?
      ni=n_{i} =Ni×nN N_{i} \times \frac{n}{N}
    • Steps in random sampling
      1️⃣ Identify the Population
      2️⃣ Assign Numbers
      3️⃣ Select Numbers
      4️⃣ Collect Sample
    • A large sample size is essential for ensuring representativeness in random sampling.
    • What are the advantages of systematic sampling?
      Simplicity and uniformity
    • Systematic sampling can introduce bias if the sampling interval coincides with population patterns.
    • Compared to random sampling, systematic sampling is more structured
    • What are the main sampling techniques used in population studies?
      Random, systematic, stratified
    • Random sampling ensures unbiased selection but may not cover the entire population effectively.
    • When is random sampling most appropriate?
      Uniformly distributed populations
    • Systematic sampling can introduce bias with repeating population patterns
    • Systematic sampling is suitable for large, consistent areas.
    • What is a key requirement for stratified sampling?
      Detailed knowledge of subgroups