Designs Unit 0

• Scientific Method:

  • A systematic approach used by scientists to investigate natural phenomena, acquire knowledge, and formulate and test hypotheses
  • In psychology, it is a general approach to understanding human behavior
• Scientific Research:

  • The researcher formulates a research question, conducts a study designed to answer the question, analyzes the resulting data, draws conclusions, and publishes the results
  • The research literature is a primary source of new research questions, creating a cycle of systematic and dynamic process
• Conceptual clarification:

  • Research methods: procedures used to collect and analyze data
  • Research Designs: the overall strategy chosen to integrate different components of the study in a coherent and logical way
  • Techniques: specific procedures or tools used within a broader method
• Qualitative Research:

  • Research method to explore and understand the meaning that individuals or groups of people attribute to social or human problems
  • Characteristics include collecting field data, researcher as a key instrument, multiple sources of data, inductive data analysis, and focusing on participant meanings
• Quantitative Research:

  • The process of collecting and analyzing numerical data to find patterns, make predictions, test causal relationships, and generalize results
  • Can be used for descriptive, correlational, or experimental research
• Hypothetico-deductive (HD) method:

  • A cyclic pattern of reasoning and observation used to generate and test proposed explanations of puzzling observations in nature
  • Based on philosophical principles of positivism where only observable and measurable objects are studied
• Experimental Design:

  • Used to study causal relationships by manipulating independent variables and measuring their effects on dependent variables
  • Involves defining variables, writing hypotheses, designing experimental treatments, assigning subjects to treatment groups, and measuring dependent variables
• Quasi-experimental Design:

  • Aims to establish cause-and-effect relationships between independent and dependent variables without relying on random assignment
  • Used for ethical or practical reasons when random assignment is not feasible
• Non-Experimental Design:

  • Descriptive or correlational research that does not manipulate variables or randomly assign participants to control or treatment groups
  • Correlational research investigates relationships between variables without the researcher controlling or manipulating them
• Quantitative research is ideal for gathering data quickly from natural settings
• It helps generalize findings to real-life situations in an externally valid way
• Types of research objectives:

  • General objectives state the main goal of the research
  • Specific objectives break down the main goal into smaller, logically connected parts
• A hypothesis states predictions about what the research will find

  • It is a tentative answer to the research question that has not yet been tested
  • Hypotheses propose a relationship between variables
• Variables in research:

  • Independent variable: Manipulated or varied in an experimental study
  • Dependent variable: Changes as a result of the independent variable manipulation
• Data analysis process involves data organization, data reduction, and data analysis

  • Types of data in research: Qualitative data and Quantitative data
• Inferential statistics are used to make predictions about a larger population after research and data analysis

  • Estimating parameters and hypothesis testing are significant areas of inferential statistics
  • Correlation and cross-tabulation are used to analyze relationships between variables
• Interpretation of results explains the meaning and implications of findings in relation to research objectives, questions, and hypotheses
• Conclusion validity is the degree to which the conclusion reached is credible or believable
• Types of conclusion validity:

  • Internal
  • External
  • Construct
  • Statistical conclusion validity
• Constructs are abstract concepts not directly observable but can be inferred indirectly through situations
• Construct validity is about how well a test measures the concept it was designed to evaluate
• Assessing construct validity is crucial for establishing the overall validity of a method
• Internal validity is the extent to which a cause-and-effect relationship established in a study cannot be explained by other factors
• High internal validity makes the conclusions of a causal relationship credible and trustworthy
• Conditions for establishing causality:

  • Independent variable A (treatment variable)
  • Dependent variable B (response variable)
• Threats to internal validity:

  • Changes in treatment and response variables must occur together
  • Treatment must precede changes in response variables
  • No confounding or extraneous factors can explain the results
• Statistical conclusion validity holds when the conclusions of a research study are founded on an adequate analysis of the data
• Strategies to improve statistical conclusion validity:

  • Appropriate sample size
  • Random sampling
  • Reliable measurements
  • Transparent reporting
• External validity is the extent to which findings of a study can be generalized to other situations, people, settings, and measures
• Without high external validity, results from the laboratory cannot be applied to other people or the real world
• In qualitative studies, external validity is referred to as transferability
• Ways to counter threats to external validity:

  • Replications
  • Field experiments
  • Probability sampling
• Conclusion validity is the degree to which the conclusion reached is credible or believable
• Types of conclusion validity:

  • Internal
  • External
  • Construct
  • Statistical conclusion validity
• Constructs are abstract concepts not directly observable but can be inferred indirectly through situations
• Examples of constructs: anxiety, intelligence, stress
• Construct validity is about how well a test measures the concept it was designed to evaluate
• Assessing construct validity is crucial for establishing the overall validity of a method
• Internal validity is the extent to which a cause-and-effect relationship established in a study cannot be explained by other factors
• High internal validity makes the conclusions of a causal relationship credible and trustworthy