Scientific Method and Research Principles Quiz

Scientific Method

• Science: Acquiring knowledge through observation, evaluation, interpretation, and theoretical explanation.
• Scientific Method: A systematic approach to gaining knowledge about observable and measurable phenomena.
• Observable: Phenomena perceived directly or indirectly using tools.
• Measurable: Phenomena that can be quantified with a standard unit or scale.
• Theory-Hypothesis-Data Cycle:
  • Theory: Well-established explanation integrating facts and observations.
  • Hypothesis: Specific, testable prediction from a theory.
  • Data Collection: Systematic observation and measurement to test the hypothesis; findings support or refine the theory, creating a continuous improvement cycle.

Data and Variables

• Variable: Characteristic or attribute that can change.
• Quantitative Variable: Numerical, measurable quantity.
• Qualitative Variable: Categorical, representing groupings or characteristics.
• Continuous Variable: Quantitative, can take any value within a range.
• Discrete Variable: Quantitative, can only take specific values (often whole numbers).
• Nominal Variable: Qualitative, categories have no meaningful order.
• Ordinal Variable: Qualitative, categories have a meaningful order.
• Dummy Variable: Numerical (0 or 1) to represent categorical data.
• Data: Facts collected for reference or analysis.
• Dataset: Collection of related data in a standardized format.
• Raw Data: Original, unprocessed information collected.
• Processed Data: Transformed/analyzed raw data, cleaned & organized.
• Observation: Single unit of analysis in a dataset.
• Transferring Quantitative to Qualitative: Dividing a range of values into intervals and assigning data points to the corresponding interval.

Populations and Samples

• Population: Entire group of individuals/objects for study's findings.
• Sample: Smaller subset selected from the population.
• Sampling Frame: List/source from which the sample is chosen.
• Accessible Population: Realistic portion of the population available for selection.
• Probability Sampling: Each member has a known chance of selection.
• Non-Probability Sampling: Individuals selected based on convenience, judgment, etc.
• Simple Random Sampling: Each individual has an equal chance of selection.
• Systematic Sampling: Selecting every nth individual from a list.
• Stratified Sampling: Dividing the population into strata, sampling from each.
• Cluster Sampling: Dividing the population into clusters, randomly selecting clusters.
• Convenience Sampling: Selecting individuals who are easy to reach.
• Sampling Bias: Favoring certain groups in selection, leading to an unrepresentative sample.
• Nonresponse Bias: Arises when some individuals don't participate, skewing the sample.
• Representative Sampling: Selecting a sample that accurately reflects the population ensuring generalized findings with minimal bias.
• Sampling Procedure Design: Define the target population, identify the accessible population, develop a sampling frame, use a representative sampling method.
• Sampling Bias Identification: Check if the sampling frame & method might systematically exclude/overrepresent subgroups, acknowledge potential issues like nonresponse bias.

Independent and Dependent Variables

• Independent Variable (IV): Manipulated variable to observe its effect.
• Dependent Variable (DV): Outcome or measured variable affected by the IV.
• Confounding Variable: Extraneous factor related to both IV and DV, potentially distorting the relationship.
• Mediator: Variable explaining the relationship mechanism between the IV and DV.
• Identifying Variables: Determine the DV (outcome), then IV (cause), detect potential confounding variables, and identify any mediator variables to understand the mechanism.