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Random Sampling Simplified Revision Notes

Revision notes with simplified explanations to understand Random Sampling quickly and effectively.

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4.6.6 Random Sampling

infoNote

To study the genetic diversity of a population, scientists often rely on sampling, as measuring every individual in a population is impractical. Sampling allows for the collection of representative data.

Key Concepts

  • Interspecific Variation: Differences between species.
  • Intraspecific Variation: Differences between individuals of the same species.
  • Gene Technology: Modern techniques allow scientists to determine genetic diversity by analysing DNA, mRNA, and amino acid sequences.
    • Differences in DNA base sequences provide the most direct measure of genetic diversity.
    • Amino acid sequences can be traced back to mRNA and DNA sequences.

Sampling Techniques

  1. Random Sampling: Ensures that each individual in the population has an equal chance of being selected.
  • Tools to Reduce Sampling Bias:
  • Quadrats: Used to mark specific areas for sampling.
  • Transects: Lines across a habitat used for systematic sampling.
  • Randomly generated coordinates can be used to place quadrats or transects.
  1. Avoiding Bias and Increasing Reliability:
  • Sampling Bias: May occur if certain areas or individuals are unintentionally favoured during data collection.
  • Chance: Even with random sampling, the sample might not represent the entire population.
  • Larger Sample Size: A larger sample reduces the influence of anomalies and ensures more reliable results.

Advantages of Random Sampling

  • Minimises bias.
  • Provides representative data when paired with large sample sizes and statistical analysis.
infoNote

Exam Tip

Be prepared to explain how random sampling can reduce bias and improve the reliability of results. Mention tools like quadrats or transects and their role in ensuring representative data collection. Use examples to illustrate differences between intraspecific and interspecific variation.

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