Research Methods

Concepts to Know

• Hindsight Bias: The tendency to believe, after an event occurs, that we knew it would happen all along. Example: "I knew they'd win the game!" (said after the game ends)

• Overconfidence: We often think we know more than we actually do.

• Pseudoscience: Beliefs or practices that seem scientific but lack evidence. Example: ESP (extrasensory perception)

• Confirmation Bias: The tendency to seek out information that supports our existing beliefs and ignore evidence that contradicts them.

The Scientific Mindset

• Curiosity: A passion for exploring and understanding the world around us.

• Skepticism: Questioning claims and demanding evidence.

• Humility: Being open to the possibility of being wrong and changing our minds based on new information.

Critical Thinking: Carefully evaluating information and arguments instead of blindly accepting them.

The Scientific Method in Psychology

1. Theory: A well-tested explanation that organizes observations and predicts behaviors or events. Think of it as a big idea supported by lots of research.

2. Hypothesis: A testable prediction, often derived from a theory. It's a specific statement about what we expect to find in our research.

3. Operational Definition: A precise description of how a variable will be measured or manipulated. This makes sure everyone understands exactly what we're studying.

4. Research/Observation: Conducting studies to test the hypothesis. We gather data to see if our prediction holds up.

Ethics in Psychological Research

Guiding Principles

• American Psychological Association (APA) Code of Ethics (1953): A set of rules that all psychologists must follow to ensure ethical research practices.

• Institutional Review Boards (IRB): Groups that review research proposals to make sure they are ethical before allowing them to proceed.

Protecting Human Participants

• Informed Consent: Participants must be fully informed about the study and its potential risks or benefits before agreeing to participate.

  • Special Note for Minors: Children cannot give consent, so researchers must get permission from parents or guardians and regularly check in with the child to make sure they want to continue.

• Limited Deception: Researchers can only mislead participants if it's absolutely necessary for the study and they must explain the deception afterward.

• Protection from Harm: Researchers must minimize any discomfort or risk and take steps to prevent long-term negative consequences for participants.

• Right to Withdraw: Participants can leave the study at any time.

• Confidentiality: Researchers must keep personal information about participants private.

• Debriefing: After the study, researchers must explain everything about it, answer questions, and correct any misunderstandings.

Ethical Use of Animals in Research

• Why Animals?: Animal research can provide information that would be impossible or unethical to get from humans.

• Humane Treatment: Animals should not be subjected to unnecessary pain or suffering. Any harm must be justified by the potential benefits to human welfare.

• Animal Care Guidelines: Just like human research, there are strict rules about how animals must be cared for in research settings.

Understanding Research Methods in Psychology

Correlations

• Positive Correlation: Two factors increase or decrease together. Example: More hours studied, higher test scores.

• Negative Correlation: Two factors move in opposite directions. Example: More video games played, lower grades.

• Scatterplots: Graphs that show the relationship between two variables. The closer the dots are to a straight line, the stronger the correlation.

• Correlation Coefficient: A number that indicates the strength and direction of a correlation.

  • Perfect positive: +1

  • Perfect negative: -1

  • No correlation: 0

• Remember: Correlation does not prove causation! Just because two things are related doesn't mean one causes the other.

Research Methods

• Naturalistic Observation: Watching and recording behavior in its natural setting.

  • Strengths: Provides realistic data.

  • Weaknesses: People may act differently if they know they're being observed. Observer bias can occur.

• Case Studies: In-depth investigation of a single person or situation.

  • Strengths: Useful for studying rare or complex cases.

  • Weaknesses: Results may not apply to others.

• Surveys: Questionnaires or interviews to gather self-reported information from a group of people.

  • Strengths: Efficient way to collect a lot of data.

  • Weaknesses: People may not answer honestly or accurately. Questions can be biased.

• Quasi-Experiment: Similar to an experiment, but participants are not randomly assigned to groups.

  • Strengths: Allows researchers to study variables that cannot be ethically manipulated.

  • Weaknesses: Cannot determine cause and effect with the same certainty as a true experiment.

Experiments in Psychology

Experiments are the most reliable way to determine cause-and-effect relationships.

Building a Representative Sample

• Goal: Select participants who accurately reflect the larger population you're studying.

• Random Sample: Everyone in the population has an equal chance of being chosen.

• Stratified Sample: The population is divided into subgroups, and a random sample is taken from each to ensure representation.

Why Random Sampling Matters: It allows researchers to generalize their findings, meaning they can confidently apply the results to the larger population.

Experimental Design

• Random Assignment: Once the sample is chosen, participants are randomly assigned to either the experimental or control group. This helps to minimize differences between the groups before the experiment starts.

• Experimental Group: Receives the treatment or intervention being studied.

• Control Group: Does not receive the treatment, serving as a comparison.

• Independent Variable (IV): The factor the researcher manipulates (the "cause").

• Dependent Variable (DV): The factor that may change in response to the IV (the "effect").

• Placebo: A fake treatment given to the control group to account for the "placebo effect," where expectations can influence results.

• The Null Hypothesis: The starting assumption that there is no real difference between groups. Researchers aim to reject this hypothesis to show that their findings are meaningful.

Controlling Bias in Research

• Single-Blind Study: Only the participants don't know which group they're in (experimental or control).

• Double-Blind Study: Both participants and researchers are "blind" to who's in which group. This helps prevent bias from influencing the results.

• Confounding Variables: Factors other than the independent variable that might affect the dependent variable. Researchers need to control for these to get accurate results.

Analyzing and Interpreting Data

• Descriptive Statistics: Using numbers to summarize and describe the characteristics of a group of data.

  • Measures of Central Tendency:

    • Mean (average): The sum of all scores divided by the number of scores.

    • Median (middle): The score that falls exactly in the middle when data is ordered.

    • Mode (most frequent): The score that occurs most often.

  • Choosing the Right Measure:

    • Mean: Best for symmetrically distributed data.

    • Median: Better for skewed data (outliers can distort the mean).

    • Mode: Only used for nominal data (categories).

• Longitudinal Study: Follows the same group of individuals over a long period.

• Cross-Sectional Study: Compares different age groups at a single point in time.

Statistical Significance

• What It Means: The difference between groups is likely due to the experimental manipulation, not just random chance.

• The 5% Rule: Results are considered statistically significant if there's less than a 5% chance the difference occurred by chance alone. (p < .05)

Understanding Data: Measures of Variation

• Range: The simplest measure of variation, calculated by subtracting the lowest score from the highest score.

• Standard Deviation: The average distance of each data point from the mean. A larger standard deviation means the data is more spread out.

• Normal Distribution (Bell Curve): A symmetrical, bell-shaped curve where the mean, median, and mode are all the same. Key percentages to remember: 34.1% of data falls within one standard deviation of the mean, 13.6% within two standard deviations, and so on. (1 sx = 68%, 2sx = 95%, 3sx = 98%)

• Skewed Distribution: When data is unevenly distributed, with a tail on one side.

  • Positive Skew: Tail to the right (outliers are high values).

  • Negative Skew: Tail to the left (outliers are low values).

Inferential Statistics: Making Decisions About Populations

• Purpose: To determine if findings from a sample can be applied to the larger population from which it was drawn.