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• Psychological science relies on empirical evidence
• Psychology adapts as new data develops
• Psychology values transparent, ethical, inclusive, replicable science

Scientific Method as Ongoing Process

• Make observations based on experiences, thoughts, or reading
• Think of Interesting Question about pattern from observations that occur
• Formulate Hypotheses by identifying the general causes for the phenomenon
• Develop Testable Predictions based on the hypothesis that predict certain outcomes
• Gather Data to Test Predictions from experiments, literature, and new observations
• Thorough testing necessitates replication to verify results
• Refine, Alter, Expand, or Reject Hypotheses based on the data collected
• Develop General Theories which must be consistent with available data and current theories

Theories

• Scientific theories explain the relationship between two or more variables
• Theories must be testable using current research techniques
• Theories should also be falsifiable
• Theories should be parsimonious and prefer simplicity

Examples of Psychological Theories

• Intergroup Contact Theory (Pettigrew, 1998) states that positive intergroup contact can reduce prejudice under certain circumstances
• Social Comparison Theory (Festinger, 1954) states that people evaluate their abilities by comparing themselves to similar others when objective measures are unavailable
• Social Learning Theory (Bandura, 1977) posits that people can learn through observing others, without explicit behavioral reproduction or reinforcement

Variables

• A variable is a characteristic or condition that changes or has different values for different individuals
• The independent variable is the variable that is manipulated to see its impact on the dependent variable
• The dependent variable is the variable that is measured to see how it is affected by the independent variable

Conceptual vs. Operational Definitions of Variables

• A conceptual definition is a dictionary or textbook definition of a term; it explains the meaning of it
• Operational definitions define theoretical constructs in terms of concrete, observable procedures
• This means operational definitions define variables in a way that they can be measured

Descriptive Methods

• Descriptive methods are concerned with a single variable of interest
• Descriptive Methods involve the systematic observation and classification of behavior
• Descriptive methods can include the use of:
• Surveys
• Focus groups
• Case studies
• Observational research

Types of Observation

• Naturalistic observation is passive, where observers do not alter ongoing behavior
• Participant observation is active, where the researcher is actively involved in the situation
• Laboratory observation involves systematic observations made within a laboratory setting, rather than in the 'real world'

Strengths of Descriptive Approaches

• Case studies and observational research can provide important insights and stimulate further research to test specific hypotheses
• Surveys allow for the quick and easy gathering of large amounts of information
• Focus groups and interviews can provide rich, detailed information that may be lacking from a survey

Potential Problems with Descriptive Methods

• Reactivity: also known as the Hawthorne Effect
• Demand characteristics
• Observer/experimenter bias
• Self-report bias such as social desirability bias
• The “better-than-average” effect

Summary of Descriptive Methods

• Descriptive Study Methods are often used in combination with other methodological approaches in psychology
• These methods may lead to claims about the frequency or prevalence of a behavior
• The use of descriptive study methods can add rich, qualitative information to a research program that would otherwise be missing this type of detail

Correlational Methods

• Correlational methods examine associations between two or more variables
• These methods examine how variables related to each other
• They involve a single group of participants with at least two measures (variables of interest)
• Claims can be made about associations between variables, but not causal claims

Correlational Studies

• No relationship = 0
• Positive relationship (+) = variables move in the same direction
• Negative relationship (-) = variables move in the inverse direction
• Correlation strength is rated from strong to weak

Correlation vs. Causation

• Correlational studies do not tell whether one variable causes changes in another variable due to
• Directionality Problem where variables are related but not causational
• Third-Variable Problem where the 2 variables are related by another variable influencing them both

Pros of Correlational Methods

• Implementation can occur if it is impossible to manipulate a variable of interest, due to feasibility or ethical concerns

Summary of Correlational Methods

• Correlational studies are important to psychological research because they allow examination of relationships between variables
• However, they do not allow to make cause-and-effect claims

Experimental Methods

• Experimental methods examine cause-and-effect relationships between two or more variables
• Independent variable is manipulated
• The impact on is studies on the dependent variable tightly controlled environment which are randomly assigned

Experiments

• Manipulation of an independent variable happens to determine its impact on a dependent variable
• High degree of control
• Are typically done in place in the laboratory
• Participants are randomly assigned to study conditions

Importance of Control

• A confound may unintentionally vary along with the independent variable and may limit the ability to make causal claims

Types of Assignments

• A random assignment ensures that each participant has an equal chance of being assigned to any condition in a study
• A random sample involves each member of the population having an equal chance of being chosen to participate

Double-Blind Experiments

• Involve both participants and experimenters who interact with them being unaware of which condition the participant is in

Participants Samples vs Populations

• A population is the group that you want to be able to generalize your findings to
• A sample is the group of individuals from this population who are part of your study
• Random samples are diverse where convenience samples are not

Quasi-Experiments

• Random assignment may not be possible
• Researchers takes advantage of pre-existing groups
• Risks of potential confounds limits the claims that a researcher can make
• Useful for studying variables where random assignment isn't feasible or ethical!

Field Experiments

• The field" is the real-world
• Random assignment is possible
• Researchers have less control over the study
• Participants are often unaware of the study

Summary of Experiments

• Experiments involve the manipulation of an independent variable to measure its effect on a dependent variable
• Random assignment and other strategies are used to avoid potential confounds which threaten the internal validity of our experiment

Critical Thinking About Research

• One should consider the measured variable
• Also the degree to which the variables in a study truly represent the abstract, hypothetical variables: (construct validity)
• Should also consider the participants, their background etc
• Are the causal claims being truly justified?

Validity and Reliability

Types of Claims

• Descriptive methods make claims regarding the frequency of some behavior
• Correlational claims make claims regarding the association between two variables
• Experimental methods make claims regarding the causal relationship between two variables

Validity

• Construct validity evaluates if study measures what it is supposed to measure
• External validity assess results being expected to generalize people and other contexts besides those in the study itself
• Internal validity determines study cause and effect based on confounds

Types of Statistics

• Descriptive statistics organize data into meaningful patterns and summaries
• These describe the data using Percentages, counts, averages, correlations, etc.
• Inferential statistics allow to extend conclusions from a sample to a population based on data
• Inferences are always probabilistic

Replication & Reproducibility

• Reproducibility is being duplicated in method and analysis
• Replicability means study about a phenomenon produce similar results from studies
• Close/Exact Replications
• Conceptual Replications