Untitled Quiz

Descriptive Research Strategy

• Aims to describe characteristics, behaviors, or phenomena without establishing cause-and-effect relationships.
• Answers questions like "What exists?", "What is happening?", and "How do people behave?".
• Useful in early research stages to form hypotheses.

Key Features

• Purpose: Describe variables as they naturally occur; does not manipulate or establish causal relationships.
• Use Cases: Understanding trends, identifying patterns, documenting phenomena for later analysis.
• Research Questions Examples: Common stressors among college students, frequency of social media use, demographic composition of urban neighborhoods.

Key Terms

• Variable: Any characteristic or phenomenon measurable. (e.g., age, height, study hours).
• Population: The entire group of interest. (e.g., all college students in the US).
• Sample: A subset of the population used to collect data. (e.g., 500 college students).
• Observation: Recording behavior directly (e.g., watching children in a playground).
• Survey: Using questionnaires or interviews to collect data. (e.g., asking about job satisfaction).
• Case Study: In-depth study of a single individual or small group. (e.g., examining a patient with a rare psychological disorder).

Types of Descriptive Research

• Observational Research: Systematic observation and recording of behaviors in natural or contrived settings.
  • Subtypes:
    • Naturalistic Observation: Observing behavior in natural environment.
    • Participant Observation: Researcher becomes part of the observed group.
    • Contrived Observation: Observations occur in controlled settings.
• Survey Research: Collecting self-reported data using questionnaires or interviews. Common question formats include closed-ended (multiple choice) or open-ended (descriptive).
• Case Study: In-depth exploration of an individual, group, or situation to study rare or unique phenomena, like a child prodigy or survivor of natural disaster.

Single Case Experimental Research Design

• Used to study the effect of an intervention on an individual or small group.
• Focuses on within-subject variations, not comparisons among multiple groups.
• Involves repeated measures of the dependent variable.

Key Features of Single-Case Designs

• Repeated Measures: Dependent variable measured multiple times before and after an intervention.
• Baseline Phase (A): Measures the behavior without intervention, establishing a comparison.
• Intervention Phase (B): The period when an intervention/treatment is applied.

Types of Single-Case Designs

• AB Design: Simple; baseline (A) followed by intervention (B).
• ABA (Reversal) Design: Baseline (A) → Intervention (B) → Baseline (A) to strengthen causal inference through replication.
• ABAB Design: Baseline (A) → Intervention (B) → Baseline (A) → Intervention (B) replicating the intervention for a stronger causal inference.
• Multiple Baseline Designs: The intervention is staggered across behaviors, settings, or participants rather than withdrawing it completely. There are several types to target different aspects (multiple behaviors, settings, participants).

Changing Criterion Design

• Performance criteria for reinforcement are gradually changed.
• Measures if the behavior systematically follows the changing criteria in an increasing or decreasing pattern.

Descriptive Statistics

• Summarizes and organizes data (e.g., mean, median, mode, range, standard deviation).
• Summarizes a sample or population.
• Example: Reporting average exam scores of a class.

Inferential Statistics

• Makes predictions or generalizations about a population based on sample data.
• Uses hypothesis testing, confidence intervals, and estimation.
• Example: Using a sample of 100 students to estimate the average exam score of all college students.