key term - Representative Sample

Definition

A representative sample is a subset of a population that accurately reflects the characteristics of the larger group from which it is drawn. This means that the sample includes individuals or observations that capture the diversity and variability of the population, ensuring that results from the sample can be generalized back to the whole group. In experimental design, using a representative sample is crucial for obtaining valid and reliable results that can be applied to broader contexts.

5 Must Know Facts For Your Next Test

1. A representative sample helps to minimize sampling bias, making it easier to draw valid conclusions about the entire population.
2. The characteristics of a representative sample should mirror those of the population, including demographics like age, gender, ethnicity, and other relevant factors.
3. Selecting a representative sample often involves using random sampling techniques to ensure every individual has an equal opportunity to be chosen.
4. In experimental design, having a representative sample enhances the external validity of the findings, allowing researchers to generalize results to a wider audience.
5. When a study uses a representative sample, it increases the confidence in the effectiveness of treatments or interventions across different groups.

Review Questions

• How does a representative sample contribute to the validity of an experimental design?
  • A representative sample contributes to the validity of an experimental design by ensuring that the findings from the experiment can be generalized to a larger population. When researchers select participants that reflect the diversity of the population, they reduce bias and improve the likelihood that their results are applicable beyond just those sampled. This means that conclusions drawn from the study are more likely to hold true for all individuals in the population, making the research more impactful.
• What are some common methods for obtaining a representative sample in research studies?
  • Common methods for obtaining a representative sample include random sampling, stratified sampling, and systematic sampling. Random sampling ensures each individual has an equal chance of being selected, while stratified sampling divides the population into subgroups based on specific characteristics and samples from each subgroup proportionally. Systematic sampling involves selecting individuals at regular intervals from an ordered list. Each of these methods aims to create a sample that accurately reflects the larger population.
• Evaluate how using an unrepresentative sample could affect research outcomes and implications in experimental design.
  • Using an unrepresentative sample can significantly skew research outcomes and lead to misleading conclusions. If certain groups are overrepresented or underrepresented, the results may not reflect the true effects of an intervention or treatment across different demographics. This can result in inappropriate recommendations or policies based on flawed data. The lack of generalizability diminishes the external validity of the study and may undermine trust in research findings, which can have far-reaching implications for fields like public health or education.

Related terms

Population:

The entire group of individuals or observations that researchers want to draw conclusions about.

Sampling Bias:

A systematic error that occurs when certain members of a population are more likely to be included in a sample than others, leading to an unrepresentative sample.

Random Sampling:

A technique where each individual in the population has an equal chance of being selected for the sample, helping to ensure that the sample is representative.