key term - Sample Size

Definition

Sample size refers to the number of individuals or observations included in a study, which is critical for ensuring the reliability and validity of research findings. A well-defined sample size helps researchers generalize results to a larger population and can impact the statistical power of the study. In the context of research methods, selecting an appropriate sample size is essential to achieve meaningful and accurate conclusions.

5 Must Know Facts For Your Next Test

1. A larger sample size generally increases the reliability of the results, reducing the margin of error and increasing confidence in findings.
2. Determining an appropriate sample size often involves statistical calculations based on expected effect sizes, desired power, and significance levels.
3. Inadequate sample sizes can lead to Type I or Type II errors, where researchers might incorrectly reject or fail to reject a null hypothesis.
4. Research in adolescent development often requires diverse samples to accurately reflect the various subgroups within the population, like age, gender, and socio-economic status.
5. Ethical considerations sometimes limit sample sizes in studies involving adolescents, as obtaining informed consent from minors can complicate recruitment efforts.

Review Questions

• How does sample size impact the reliability of research findings in studies of adolescent development?
  • Sample size significantly impacts the reliability of research findings because larger samples tend to provide more accurate estimates of population parameters. In adolescent development research, a sufficient sample size reduces sampling error and increases the likelihood that results can be generalized across different demographics. This is crucial when considering the diverse experiences and backgrounds of adolescents, ensuring that findings are reflective of various groups.
• What statistical methods can researchers use to determine an appropriate sample size for studies focused on adolescent behaviors?
  • Researchers can use power analysis as a statistical method to determine an appropriate sample size for studies on adolescent behaviors. This process involves estimating effect sizes based on prior research and deciding on acceptable levels of significance and power. By calculating how many participants are needed to detect a statistically significant effect, researchers can ensure that their studies are adequately powered to make valid inferences about adolescent populations.
• Evaluate the ethical considerations that researchers must take into account when determining sample size in studies involving adolescents.
  • When determining sample size for studies involving adolescents, researchers must consider ethical issues such as obtaining informed consent and ensuring participant safety. The recruitment process may be limited by legal requirements for parental consent and the sensitivity surrounding topics related to adolescent health and behavior. Researchers must balance the need for an adequate sample size with these ethical constraints, often seeking ways to include diverse participants while respecting individual rights and welfare.

Related terms

Statistical Power: The probability that a study will detect an effect when there is an effect to be detected, which is influenced by the sample size.

Sampling Techniques: Methods used to select individuals from a population to be included in a sample, such as random sampling or stratified sampling.

Population: The entire group of individuals or observations that researchers are interested in studying, from which a sample is drawn.