Introduction to Research Methods and Statistics: Populations and Samples

Fundamentals of Research and Statistics in Behavioral Sciences

  • Gathering Information in Behavioral Research:

    • Research in the behavioral sciences and related fields fundamentally centers on the systematic collection and gathering of information.

    • Example scenario: Investigating whether college students demonstrate superior learning outcomes when reading material on printed pages versus on a computer screen requires gathering detailed information regarding students' study habits and academic performance metrics.

    • Information gathering routinely results in vast volumes of data across various measurement types, including:

    • Explicit preferences

    • Personality scores

    • Subjective opinions and attitudes

    • Performance indicators

  • Dual Purposes of Statistics:

    • Organization and Summarization: Statistics provide tools to organize and summarize collected data so that researchers can clearly observe what occurred within a study and effectively communicate results to the broader scientific community.

    • Hypothesis Testing and Conclusion Drawing: Statistics assist researchers in answering initial research questions by determining precisely what general conclusions are justified based on the specific empirical results obtained.

    • Accuracy and Information Integrity: Statistical procedures ensure that observations are presented and interpreted in an accurate, objective, and informative manner.

  • Standardization and Scientific Order:

    • Statistics enable researchers to bring order out of complex or chaotic raw data.

    • Statistical methods offer a standardized set of techniques recognized and understood universally throughout the scientific community.

    • Standardized analytical techniques allow researchers to read, interpret, and evaluate the work of peers with a complete understanding of how the analysis was executed and what the resulting figures signify.

Concepts of Populations in Scientific Research

  • Definition of a Population:

    • A population consists of all possible members of a designated group that an investigator wishes to study.

    • Behavioral research typically initiates with a overarching question regarding a specific group or multiple groups of individuals.

  • Examples of Target Populations and Research Questions:

    • Factors associated with academic dishonesty among college students (Target population: College students).

    • The developmental impact of lead exposure on emotional problems in school-aged children (Target population: School-aged children).

  • Variation in Population Size:

    • Populations can range from exceptionally large to extremely small depending on how the investigator explicitly specifies the boundaries of the group:

    • Extremely Large Populations:

      • The entire set of all registered voters in the United States.

      • College sophomores across the United States.

      • Coffee drinkers patronizing a major national chain of cafes.

    • Narrowed or Moderately Sized Populations:

      • People in their twenties who are registered voters in the United States.

      • First-time voter registrants in Burlington, Vermont.

    • Extremely Small Populations:

      • Individuals diagnosed with a specific rare disease.

      • Endangered species, such as the Siberian tiger, which has a population of roughly only 500500 animals.

  • Non-Human Populations:

    • A population does not need to consist of human beings. Depending on the research field, a population can be composed of:

    • Laboratory rats

    • North American corporations

    • Engine parts produced in an automobile factory

    • Any other specific set of entities under investigation

  • Specification Requirement:

    • Researchers must explicitly define and specify the exact parameters of the target population under study.

    • In practical research scenarios, target populations are typically far too large to evaluate in their entirety.

Concepts of Samples and Sample-Population Dynamics

  • Definition and Function of a Sample:

    • A sample is a set of individuals selected from a defined population.

    • Because populations are usually too large to permit the measurement of every single constituent member, researchers select a smaller, manageable subset to participate in the study.

    • Research procedures and measurements are limited directly to the individuals in the selected sample.

  • Representativeness and Random Sampling:

    • A sample is designed and intended to be representative of the target population from which it was drawn.

    • A sample must always be explicitly identified in relation to its specific target population.

    • Random Sampling: A foundational selection method where every individual in the population has the exact same probability of being chosen for the sample, ensuring high representativeness.

  • Variation in Sample Size:

    • Sample sizes vary significantly depending on study design, resources, and requirements:

    • Small sample example: A study evaluating an experimental reading program using a sample of n=20n = 20 middle school students.

    • Large sample example: A study evaluating a new cholesterol medication using a sample of n>2000n > 2000 individuals.

  • The Full Relationship Cycle Between Sample and Population:

    • The interaction between samples and populations forms a complete two-way cycle:

    1. Formulation: The research begins with a broad question concerning an entire population.

    2. Sampling: A representative sample is selected from the target population.

    3. Measurement: The study is conducted, and empirical data is collected directly from the sample.

    4. Generalization: The statistical findings derived from the sample are generalized back to the broader target population to answer the original general question.