Lectures 3&4 PSYCH2018

Research in Psychology: Methods & Design

• The text is about research methods and design, specifically topics covered in an 8th Edition textbook.
• Topics covered include the development of research ideas, the nature of psychological theories, the roles of research teams, and creative thinking in science.

Chapter 3: Developing Ideas for Research in Psychology

• Chapter Objectives:

  • Distinguishing basic and applied research, laboratory and field research, and qualitative and quantitative research.
  • Formulating empirical questions and understanding the importance of operational definitions.
  • Describing research developed from everyday observations and serendipitous events.

• Chapter Objectives Two:

  • Describing the key features of a psychological theory.
  • Detailing how theories influence and are influenced by empirical research, needing to be productive, parsimonious, and testable.
  • Understanding the value of research that replicates and extends prior research

• Chapter Objectives Three:

  • Identifying direct and conceptual replication, as well as their importance in psychological science.
  • Demonstrating examples of creative scientific thinking.
  • Using computerized databases (e.g., PsycINFO) to research information about psychology.

Varieties of Psychological Research

• The Goals: Basic vs. Applied Research

  • Basic Research: Designed to understand fundamental psychological phenomena (e.g., stimulus factors affecting selective attention).
  • Applied Research: Designed to shed light on solutions to real-world problems (e.g., effect of cell phone use on driving).

• The Setting: Laboratory vs. Field Research

  • Laboratory Research: Offers greater control, but often lacks mundane realism.
  • Field Research: More realistic, but less control over other variables.

• The Data: Quantitative vs. Qualitative Research

  • Quantitative Research: Employs quantitative data and statistical analysis.
  • Qualitative Research: Often involves narrative descriptions or interviews but may utilize quantification of responses occasionally.

Asking Empirical Questions

• Empirical Questions: These questions can be answered using data, with variables precisely defined (e.g. Hunger = 12 hours without food; Frustration = consequence of being blocked from a goal).
• Operational Definitions: Define variables in terms of a clear set of operations.
• Converging Operations: Understanding increases when studies with different operational definitions converge on the same result.

Where to Research Ideas Come From?

• Personal Observations: Including serendipitous events.
• Psychological Theories: Theories often lead to empirical research, influenced by research outcomes, and require characteristics like productivity, parsimony, and testability.
• Existing Research: Including the question of “what’s next?” for future research opportunities.

Developing Research from Observations of Behavior and Serendipity

• Observations: Examples such as helping behavior following a tragic event (e.g., Kitty Genovese murder).
• Serendipitous Events: Discovering something new while searching for something else (e.g., Skinner’s first extinction curve).

Developing Research from Theory

• Nature of Theory: Theories summarize, organize, and explain, often including various constructs and hypothetical factors involved in the attempt to understand.
• Theory-Research Relationship: Hypotheses are deduced from theories, and research outcomes either support or fail to support theories. Importantly, theories are never “true” or “false.”
• Attributes of Good Theories: These include productivity, falsification (good theories can be shown wrong), and parsimony (good theories provide simple explanations).

Developing Research from Other Research

• Research Teams and the “What’s Next?” Question: Research programs often consist of series of interrelated studies.
• Replication: Includes the concepts of direct and conceptual replication of existing research

Creative Thinking in Science

• Prepared Mind: Chance favors the prepared mind (Pasteur).
• Maze Learning: How initial knowledge can lead to improvements or limitations in subsequent research design

Reviewing the Literature

• Computerized Database Searches: Researchers should utilize databases such as PsycINFO to find relevant research.
• Search Tips: Utilize advanced search options, truncated search terms, and trial and error strategies.
• Search Results: Pay attention to the source of information (e.g., journals, books, dissertations)

Summary

• Research involves numerous approaches (basic vs. applied; lab vs. field; quantitative vs. qualitative).
• Research questions are based on a desire to better understand psychological phenomena.
• Research ideas are drawn from observations, theories, and prior research.
• Research proficiency is improved by exploring the relevant literature, for instance through PsycINFO or similar databases.

Chapter 4: Sampling, Measurement, and Hypothesis Testing

• Chapter Objectives:
  • Distinguishing probability and non-probability sampling.
  • Describing three types of probability sampling and knowing when each is optimal.
  • Recognizing various behavioral measures utilized in psychology.
  • Identifying constructs and measurable behaviors used to study them.

Additional Chapter Objectives

• Reliability and Validity: Identifying characteristics required of behavioral measures to be reliable (free from measurement error) and valid (measuring what's intended).
• Measurement Scales: Recognizing nominal, ordinal, interval, and ratio scales and their applications.
• Summarizing Data: Using relevant statistical measures of central tendency and variability, as well as visual displays (histograms).
• Hypothesis Testing: Understanding the logic and process for inferential analysis of data concerning population characteristics.
• Criticisms and Alternatives: Recognizing limitations of hypothesis testing, including suggestions of alternative approaches (e.g., confidence intervals).

Sampling Procedures

• Probability Sampling:
  • Random Sampling: Each member of a population has an equal chance of selection in a sample.
  • Stratified Sampling: Proportions of subgroups in a population are precisely represented in the sample (e.g., 75% female, 25% male).
  • Cluster Sampling: Random selection of clusters of individuals sharing a common feature (e.g., all first-year students living on campus).
• Non-probability Sampling:
  • Convenience Sampling: Selecting subjects who are available and convenient.
  • Purposive Sampling: Selecting subjects based on specific criteria.
  • Quota Sampling: Similar to stratified, but non-random.
  • Snowball Sampling: Participants recruit additional participants.

Construct Validity

• Developing measures from constructs like habituation (e.g., measuring changes in preferential looking time), reaction time (measuring the time required for a response).

Evaluating Measures

• Reliability: Minimizing measurement error; it is the consistency and repeatability of the measurements.
• Validity: Reflects if a measure assesses what it intends to measure. Includes content, criterion, and construct validity. The latter includes convergent and discriminant validity.

Scales of Measurement

• Nominal: Classifying individuals or events into categories (e.g., guilty/not guilty).
• Ordinal: Indicating rank order (e.g., class rank).
• Interval: Quantities with equal intervals between scores, but zero is arbitrary (e.g., temperature, some IQ or personality tests).
• Ratio: Quantities with equal intervals and a meaningful zero (e.g., reaction time, number of words recalled).

Statistical Analysis

• Descriptive statistics: Summarizing data from a sample (measures of central tendency like mean, median, mode; measures of variability like range, standard deviation, variance). Visual displays include histograms.
• Inferential statistics: Making inferences about a population based on a sample (t-tests, ANOVAs). Null Hypothesis Significance Tests (NHST). Includes Type I and Type II errors, effect size, confidence intervals, and power.

Test your understanding of measurement scales, including nominal, ordinal, interval, and ratio scales. This quiz also covers key statistical concepts and methods, such as descriptive and inferential statistics and the role of outliers. Perfect for students learning about statistics and research methods.