Descriptive Methods

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Ch. 6 Observational/Descriptive Methods

I.

Observational / Descriptive Methods A.

Observation is both a Research Design and a measurement tool Designs

B. 1. 2. 3. 4. 5.

Naturalistic Observation Structured Observation Field Experiments (not covered in book) Case Studies Archival Research (not really observation, but it is descriptive)

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C. Observational Measures 1. These measures can be used in either the lab, or the real world. Lab Example – Mary Main’s Strange Situation Measure of attachment Real World – Our Helping Study

2. The measures can be either Quantitative or Qualitative. - Our study took a more Quantitative Focus. - Qualitative observations might have focused on the purpose of each subjects helping.

II Advantages of Descriptive Methods 1. Provides Basic Knowledge: gives you a rich source of data 2. Flexibility in Research Question 3. Identifies Ecological Function: Studying in the real environment you can ID the adaptive function of certain phenomena

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III. Naturalistic Observation: We observe phenomenon in the environment in which they actually occur. e.g. Jane Goodall and her observations of Chimps in Africa. A. External validity (Generalizability) – to population (representativeness) = Low (no random sampling) – to situation (Realism) - Mundane Realism = high - Experimental Realism (involvement) = high - Functional Realism (Ecological) = high

B. Internal Validity = Low, no random assignment

C. Strengths: -Research agenda can be rather flexible -Can identify ecological function (role of behaviors in adapting to the environment. -High in Realism (looks and functions like the real world, because it is measured in the real world.

- Provides Basic Knowledge

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D. Weakness: 1. Reactance -studying a phenomenon will change it in some way -People react differently when they know you are watching them - Social Desirability / - Self-Presentation Strategies - Impression Management - Self Deceptive Positiivity - Self-Awareness / Self-Consciousness

Solutions -Unobtrusive Observation -The Participant Observer (Ethnographic Approach) - Habituate Participants to observation. -Unobtrusive Measures (Indirect Measures)

D. Weakness 2. Frequency of Behaviors. - Infrequent behaviors will be difficult to observe 3. Non-equivalence of Behaviors - There may be non-equivalence of complex behaviors. Difficult to compare two subjects behaviors that differ, even to a small degree, with respect to elicitors and outcomes. - Solutions – Structured Observation

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IV. Structured Observation: Constrain the situation (real world or lab) so that desired event will occur consistently and frequently (equivalence of elicitors). External validity – Generalizability to population = -can be high (more control over sample selection)

– Generalizability to situation = Realism Mundane Realism = can be low (especially in lab) Experimental Realism = can be high Functional Realism (Ecological) = should be high

Internal Validity = Low, no random assignment

B. Structured Observation: Strengths: – Increase likelihood of seeing desired behaviors & increase equivalence of behaviors. – reduce time & cost

Weakness: - May loose realism & increase artificiality - e.g. when does the Levin study happen in the real world.

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V. Field Experiment: External validity – to population = can be high (more control over sample selection) – to situation = Realism - Mundane Realism = Should be high - Experimental Realism = Can be high - Functional Realism (Ecological) = should be high Internal Validity = Can be high, if use random assignment to condition, though you loose control in the real world. Strengths: - Higher level of control = can infer causality Weakness: - May loose realism & increase artificiality

VI. Case Study: External validity – to population = Low (one subject tells us little about the population) – to situation = Realism - Mundane Realism = Can be high - Functional Realism (Ecological) = should be high Internal Validity = very low Strengths: - Can investigate very rare psychological phenomenon. - Rich source of data. Potentially, Longitudinal. Weakness: - No causal inferences or generalizability to the population

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VII. Observer Bias - Confirmatory Bias in Hypothesis Testing - Perceptual Bias - Error

- Solutions - Inter-Rater Reliability - Two raters must agree at some minimum level (depending on the type of ratings and data). - Generally 70-80% agreement is considered adequate.

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Descriptive Methods

Ch. 6 Observational/Descriptive Methods I. Observational / Descriptive Methods A. Observation is both a Research Design and a measurement tool Desi...

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