Psychology Research Methods and Ethics

Research with Human Samples

• Psychological research aims to understand human behavior, necessitating the inclusion of diverse participants representative of humanity.
• Early research predominantly focused on male experiences due to male researchers and participants.
• There's a growing awareness of the need for diverse ethnic groups and geographical settings in psychological research.
• Critics point out that much psychology relies on "WEIRD" samples (Western, Educated, Industrialized, Rich, and Democratic societies).
• Reliance on limited samples can lead to an incomplete understanding of human behavior.
• Researchers are diversifying samples by conducting online studies with community adults instead of relying solely on undergraduate student volunteers.
• Diverse samples are essential for predicting human behavior across different populations and informing policy decisions.

Research Settings: Naturalistic Observation vs. Laboratory

• Psychological research can occur in various physical settings, including laboratories and natural environments.
• Laboratory Settings
  • Offer controlled environments to exclude complex real-world factors.
  • Allow researchers to manipulate situations, sometimes using virtual or augmented reality.
  • Drawbacks:
    • Participants are aware of being studied.
    • The artificial environment may cause unnatural behavior.
    • Participants may not represent diverse backgrounds.
    • Some aspects of the mind and behavior are hard to examine in a lab.
    • Pandemics, like COVID-19, can disrupt in-person lab experiments.
    • Many experiments have moved online, requiring validation of online manipulations.
• Naturalistic Observation
  • Involves studying behavior in real-world settings such as sporting events, childcare centers, and public spaces.
  • Researchers may use web-based assessments and big data collected in the natural flow of human life.
  • Example: Studying civility by observing interactions in a campus cafeteria.

Analyzing and Interpreting Data

• Statistics are essential for analyzing and interpreting data in psychology.
• Statistics are mathematical methods for reporting data that provide important information about scores.
• Descriptive Statistics
  • Used to describe and summarize data.
  • Reveal the overall characteristics and variation within the data.
• Inferential Statistics
  • Used to draw conclusions beyond the immediate data.
• Psychological Inquiry: The type of research, operational definitions, sample and setting should be guided by the research question, while balancing key objectives with available resources.

Measures of Central Tendency

• A measure of central tendency is a single number indicating the overall level of a variable in a dataset.
• Three common measures are the mean, median, and mode.
• Mean
  • The average, calculated by summing all scores and dividing by the number of scores.
  • Provides a general idea of the level of a variable.
  • Formula: \text{Mean} = \frac{\sum xi}{n} , where xi represents each score and n is the number of scores.
• Limitations of the Mean
  • Can be skewed by extreme values, especially in small groups.
  • Example demonstrating how extreme values affect the mean:
    • Group 1: $39,000, $39,000, $53,000, $54,000, $55,000
      • Mean: 48,000
    • Group 2: $39,000, $39,000, $53,000, $54,000, $150,000,000
      • Mean: 30,037,000
• Median
  • The middle score in a dataset when scores are arranged in order.
  • Less sensitive to extreme values than the mean.
  • In both example groups, the median is 53,000.
• Mode
  • The most frequently occurring score in a dataset.
  • In both example groups, the mode is 39,000.

Research Samples

• Population: The entire group an investigator wants to draw conclusions about.
• Sample: A subset of the population chosen for study.
• The sample must be representative of the population to generalize results.
• A representative sample should reflect the population's characteristics, such as age, socioeconomic status, ethnicity, and geographic location.
• Random Sample: A sample where every member of the population has an equal chance of being selected.
  • Improves the likelihood of a representative sample.
  • Differs from random assignment, which ensures experimental and control groups are equivalent.

Inferential Statistics

• Inferential Statistics: Mathematical methods to determine if data supports a research hypothesis.
• Used to draw conclusions about differences between groups or associations between variables.
• The logic focuses on the probability that observed differences or associations are due to chance.
• Statistical Significance: Traditionally, results with a probability of occurring by chance less than 5 times in 100 (.05) are considered statistically significant.
• The standard has been questioned, with some arguing for a stricter standard of .005 to ensure more replicable research.
• American Psychological Association guidelines require reporting exact p-values.
• P-values and Replication Crisis:
  • It's difficult to publish studies without statistically significant results.
  • Researchers may engage in p-hacking, such as dropping participants or manipulating variables, to reduce p-values.
  • Preregistering data analyses can help address concerns about p-hacking.
• Inferential statistics connect sample results to the larger population.
• Larger samples are more likely to represent the population.
• Statistical significance doesn't always equal real-world significance; results must be critically evaluated.

Ethical Consideration

• Ethics is crucial in all science, particularly after atrocities like Nazi experimentation on concentration camp prisoners.
• Ethical principles balance the rights of research participants with the rights of scientists to ask research questions.
• Risks to participants must be balanced against the scientific merit of the study.
• A study must be scientifically sound to justify any risk to participants.