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Non-Experimental (Descriptive) Methods Variables are measured, not manipulated Data can be quantitative or qualitative.

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Presentation on theme: "Non-Experimental (Descriptive) Methods Variables are measured, not manipulated Data can be quantitative or qualitative."— Presentation transcript:

1 Non-Experimental (Descriptive) Methods Variables are measured, not manipulated Data can be quantitative or qualitative

2 Types of Descriptive Methods Observational Research link People WatchinglinkPeople Watching Archival Research

3 Why use These Methods? They may stimulate formal hypotheses Description for the sake of description Prediction

4 Objective Methods Are Needed For Good Description Reliable measurements of psychological variables is not automatic Cannot rely on our memory Bias influences people's judgments Cannot rely on your own experience or a small sample of behavior

5 Observational Research Observational Data - simply watching and recording –wedding behaviorwedding behavior –kindergartenkindergarten Typically must develop behavioral categories

6 Quantitative Data Coding Methods Frequency method Duration method Intervals method

7 Qualitative Methods These are methods that do not rely on numerical data. Instead, the emphasis is on verbal description.

8 1. Naturalistic Observation Must be unobtrusive Hackers boss Hackersboss –advantage – gives good insight into behavior in the real world –disadvantage – you can speculate, but not prove hypotheses

9 2. Ethnography Person becomes immersed into the social system or culture –e.g., Napolean Chagnon and the Yanomamo linklink Can be a participant or non-participant Food haitiFoodhaiti

10 3. Sociometry Measuring social and interpersonal relationships within a group

11 4. Case History e.g., Freud’s case studies

12 Archival Research Data that is already stored in some form; collected by someone else

13 Data Sources Ex Post Facto Archival

14 Ex Post Facto Data (after the fact) Data already collected in an experiment by someone else “Nuisance variables" such as gender, age, socioeconomic data, etc. may have been collected but not analyzed Can go back and look for relationships between these variables and DV

15 Archival Data Data collected in a survey, census, market research, etc. Coded data –Advantage - can examine data you could not collect yourself –Disadvantage - may be coded in a way that is inappropriate for your work Uncoded data –Advantage - data already collected; can code yourself –Disadvantage – coding can be intensive work

16 Content Analysis Techniques used to code transcripts, audio, video –Foot TrafficFoot Traffic –c spanc span –Must develop carefully defined coding categories –Must train coders/raters carefully –day careday care –Atlas SoftwareAtlas Software

17 Limitations of Archival Data Sometimes mass data overshadows individual behaviors Data may not have been collected or coded carefully by others

18 3 Problems with Non-Experimental Research Ethics Effects of observer on the observed –Try to observe unobtrusively –Become less noticeable; allow P's to habituate to you Problems in objective data coding


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