1.1 Scientific method
6 min read•august 20, 2024
The scientific method is a systematic approach to research in political science. It involves formulating hypotheses, collecting data, and analyzing results to draw conclusions. This method aims to minimize bias and subjectivity by relying on objective and measurement.
Key steps include formulating research questions, developing testable hypotheses, designing studies, collecting data, and analyzing results. The scientific method enhances reliability and facilitates replication, but it also has limitations when studying complex social phenomena or measuring abstract concepts.
Definition of scientific method
- Systematic approach to acquiring knowledge through empirical investigation and testing
- Involves formulating hypotheses, collecting data, analyzing results, and drawing conclusions
- Aims to minimize bias and subjectivity in research by relying on objective observation and measurement
Steps in scientific method
Formulating research question
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- Identifying a specific problem or phenomenon to investigate
- Narrowing down the scope of the research to a manageable and testable question
- Ensuring the research question is clear, focused, and relevant to the field of study
Developing testable hypothesis
- Proposing a tentative explanation or prediction based on existing knowledge and theory
- Formulating the in a way that can be empirically tested and falsified
- Specifying the independent and dependent variables and their expected relationship
Designing research study
- Selecting an appropriate research design (experimental, quasi-experimental, observational) based on the research question and hypothesis
- Determining the sample size, sampling method, and data collection techniques
- Establishing validity and reliability measures to ensure the quality of the research
Collecting empirical data
- Gathering data through systematic observation, measurement, or experimentation
- Using standardized procedures and instruments to minimize error and bias
- Recording data accurately and consistently for analysis
Analyzing data collected
- Using statistical techniques to summarize and interpret the data
- Testing the hypothesis by comparing the observed results with the predicted outcomes
- Identifying patterns, trends, and relationships in the data
Drawing conclusions from analysis
- Interpreting the results in light of the research question and hypothesis
- Assessing the strength and limitations of the evidence
- Discussing the implications and significance of the findings for theory and practice
Communicating results of study
- Presenting the research findings through written reports, presentations, or publications
- Providing sufficient detail and transparency for others to evaluate and replicate the study
- Engaging in peer review and scholarly debate to refine and extend the research
Importance of scientific method
Systematic approach to research
- Provides a structured and logical framework for conducting research
- Ensures that research is guided by clear questions, hypotheses, and methods
- Promotes transparency and accountability in the research process
Minimizing bias in research
- Emphasizes objective observation and measurement over subjective intuition or speculation
- Uses standardized procedures and instruments to reduce researcher bias and error
- Encourages critical evaluation and replication of research findings by others
Enhancing reliability of findings
- Relies on empirical evidence and statistical analysis to support conclusions
- Uses large and representative samples to increase generalizability of findings
- Establishes validity and reliability measures to ensure consistency and accuracy of results
Facilitating replication of studies
- Provides detailed descriptions of research methods and procedures for others to follow
- Allows for independent verification and extension of research findings by other researchers
- Contributes to the cumulative growth of knowledge in a field through replication and refinement
Limitations of scientific method
Difficulty in studying complex phenomena
- Some social and psychological phenomena may be too complex or context-dependent to isolate and measure precisely
- Scientific method may oversimplify or neglect important factors that influence human behavior and experience
- Reductionist approach may miss the holistic and emergent properties of complex systems
Potential for researcher bias
- Researchers may have conscious or unconscious biases that affect their research questions, methods, and interpretations
- Scientific method relies on human judgment and decision-making, which can be influenced by personal, social, and cultural factors
- Bias can be minimized but not eliminated entirely, even with rigorous methodological controls
Challenges in measuring abstract concepts
- Many social and psychological constructs (attitudes, emotions, values) are difficult to operationalize and measure directly
- Researchers may rely on indirect or proxy measures that may not fully capture the underlying concept
- Measurement error and validity threats can undermine the accuracy and meaningfulness of research findings
Ethical considerations in research
- Scientific research involving human participants must adhere to ethical principles of respect, beneficence, and justice
- Researchers must obtain , protect participant confidentiality, and minimize risks of harm
- Some research questions or methods may be ethically problematic or prohibited, limiting the scope of scientific inquiry
Scientific method vs other approaches
Scientific method vs normative approach
- Scientific method emphasizes empirical observation and testing, while normative approach relies on value judgments and moral reasoning
- Scientific method aims to describe and explain what is, while normative approach prescribes what ought to be
- Scientific method is based on objectivity and neutrality, while normative approach is based on subjectivity and advocacy
Scientific method vs interpretive approach
- Scientific method focuses on causal explanation and prediction, while interpretive approach focuses on understanding and meaning
- Scientific method uses quantitative data and statistical analysis, while interpretive approach uses qualitative data and thematic analysis
- Scientific method assumes a single, objective reality, while interpretive approach assumes multiple, subjective realities
Scientific method vs critical approach
- Scientific method aims to produce value-neutral knowledge, while critical approach aims to expose and challenge power relations
- Scientific method emphasizes empirical evidence and logical reasoning, while critical approach emphasizes ideological critique and emancipatory praxis
- Scientific method assumes a stable and knowable social world, while critical approach assumes a dynamic and contested social world
Applications of scientific method
Use in quantitative research
- uses numerical data and statistical analysis to test hypotheses and generalize findings
- Examples include , experiments, and secondary data analysis (census data, economic indicators)
- Quantitative research is well-suited for studying large populations and identifying broad patterns and trends
Use in qualitative research
- Qualitative research uses non-numerical data (text, images, audio) and interpretive analysis to explore meanings and experiences
- Examples include interviews, focus groups, ethnography, and content analysis
- Qualitative research is well-suited for studying small samples in-depth and generating rich, contextual data
Use in mixed-methods research
- Mixed-methods research combines quantitative and qualitative approaches to provide a more comprehensive understanding of a phenomenon
- Examples include explanatory sequential designs (quantitative followed by qualitative) and convergent parallel designs (quantitative and qualitative conducted simultaneously)
- Mixed-methods research can leverage the strengths of both approaches and triangulate findings for greater validity and insight
Criticisms of scientific method
Positivist assumptions of scientific method
- Scientific method is rooted in positivist philosophy, which assumes that reality is objective, observable, and measurable
- Positivism may be inappropriate for studying complex social phenomena that are subjective, contextual, and constructed
- Positivist assumptions may lead to reductionism, determinism, and neglect of human agency and meaning
Reductionist nature of scientific method
- Scientific method breaks down complex phenomena into simpler, more manageable components for analysis
- Reductionism may oversimplify or distort the nature of social reality by ignoring the wholeness and interdependence of parts
- Reductionist approach may lead to fragmented and decontextualized knowledge that lacks practical or policy relevance
Overlooking context and meaning
- Scientific method emphasizes generalizability and universality of findings across contexts
- Context-stripping may neglect the unique historical, cultural, and situational factors that shape social phenomena
- Meaning-stripping may neglect the subjective interpretations and lived experiences of individuals and groups
Key Terms to Review (19)
Case studies: Case studies are in-depth examinations of a single instance, event, or entity, providing a detailed analysis that can reveal broader insights about similar situations. This method is often used to gather rich qualitative data, and it plays a significant role in understanding complex phenomena while allowing researchers to explore the context and factors influencing outcomes.
Cross-sectional study: A cross-sectional study is a type of observational research that analyzes data from a population at a specific point in time. This method allows researchers to assess the prevalence of certain characteristics, behaviors, or outcomes within a group, making it useful for identifying relationships between variables. By capturing a snapshot of data at one moment, cross-sectional studies can help in understanding patterns and trends without implying causation.
Debriefing: Debriefing is a structured conversation that occurs after a research study or experiment, where participants are informed about the study's purpose, procedures, and any deception involved. This process is crucial for ethical research practices, ensuring that participants understand their role and the outcomes of the research, which can help mitigate any potential distress caused by the experience.
Dependent Variable: A dependent variable is the outcome or effect that researchers measure in an experiment or study, which is expected to change in response to the independent variable. Understanding this concept is crucial because it helps define research questions, hypotheses, and the relationships between variables. By identifying what is being measured, researchers can operationalize these variables and explore causality and correlation effectively.
Experiment: An experiment is a systematic procedure conducted to test a hypothesis or explore cause-and-effect relationships by manipulating one or more independent variables while controlling others. This process is essential in the scientific method, as it allows researchers to gather empirical data and validate or refute their predictions through observation and analysis.
External validity: External validity refers to the extent to which the findings of a study can be generalized to, or have relevance for, settings, people, times, and measures beyond the specific conditions of the study. It is crucial for understanding how applicable research results are in real-world situations and how they relate to broader populations.
Hypothesis: A hypothesis is a testable prediction about the relationship between two or more variables. It serves as a foundation for research, guiding the design and direction of the study. A well-formed hypothesis not only predicts the outcome but also establishes a framework for analyzing data, allowing researchers to confirm or refute their assumptions through empirical evidence.
Independent Variable: An independent variable is a factor or condition that is manipulated or changed in an experiment to test its effects on a dependent variable. Understanding this concept is crucial for formulating research questions, developing hypotheses, and establishing causal relationships between variables.
Informed Consent: Informed consent is a fundamental ethical principle in research that ensures participants are fully aware of the nature of the study, including its purpose, procedures, risks, and potential benefits, before agreeing to participate. This principle is essential for protecting participants' autonomy and fostering trust between researchers and subjects.
Internal validity: Internal validity refers to the extent to which a study accurately establishes a causal relationship between the treatment and the outcome, free from confounding variables. It is crucial for ensuring that the results of an experiment truly reflect the effects of the independent variable on the dependent variable, rather than other external factors that could influence the outcome.
Longitudinal study: A longitudinal study is a research design that involves repeated observations of the same variables over a period of time, allowing researchers to track changes and developments in those variables. This approach provides insights into trends, patterns, and long-term effects, making it valuable for understanding causal relationships and correlations between factors.
Observation: Observation is the systematic process of gathering data and information through direct or indirect monitoring of phenomena. This method allows researchers to collect empirical evidence, which is crucial for testing hypotheses and theories within the scientific method. By carefully observing and recording behaviors, events, or conditions, researchers can draw conclusions and make informed decisions based on factual evidence.
Operationalization: Operationalization is the process of defining and measuring variables in a way that allows researchers to empirically assess concepts. This is crucial for transforming abstract ideas into concrete, measurable factors that can be used in research, enabling the development of research questions and hypotheses, and ensuring the effectiveness of the scientific method.
Qualitative Analysis: Qualitative analysis is a research method focused on understanding the underlying meanings, experiences, and social contexts associated with a subject. This approach emphasizes the collection of non-numerical data, such as interviews, observations, and textual materials, to gain insights into complex phenomena that quantitative methods may overlook.
Quantitative research: Quantitative research is a systematic investigation that primarily focuses on quantifying relationships, behaviors, or phenomena through statistical, mathematical, or computational techniques. This type of research uses structured methods like surveys and experiments to collect numerical data, which can then be analyzed to identify patterns and make predictions. The findings often rely on the principles of the scientific method to ensure reliability and validity.
Regression analysis: Regression analysis is a statistical method used to examine the relationship between one dependent variable and one or more independent variables. This technique helps in predicting the value of the dependent variable based on the values of the independent variables, establishing connections between them and providing insights into how changes in predictors influence outcomes.
Statistical significance: Statistical significance is a mathematical determination that helps researchers understand whether their results are likely to be genuine or if they occurred by chance. It plays a crucial role in evaluating hypotheses and research questions, determining if observed effects in experiments or studies are reliable enough to support claims about relationships between variables. This concept is vital in experimental design and analysis, enabling researchers to distinguish meaningful results from random fluctuations in data.
Surveys: Surveys are research methods used to collect data from a predefined group of respondents, allowing researchers to gain insights into opinions, behaviors, or characteristics of that population. Surveys can be quantitative or qualitative and are essential for understanding public attitudes and trends in various fields, including political research.
Theoretical framework: A theoretical framework is a collection of concepts and theories that guides researchers in understanding and interpreting their findings. It provides a foundation for building research questions, developing hypotheses, and establishing the rationale for the study, ultimately connecting the research to existing knowledge. This framework helps to clarify how various variables interact and influences the overall research design.