Presentation on theme: "Chapter 7 Experiments with One Independent Variable."— Presentation transcript:
Chapter 7 Experiments with One Independent Variable
Determining Variables of Interest There are many ways to create and manipulate variables The current nature of society often dictates what variables are studied and how they are measured For example, eyewitness testimony was not studied for decades but is now a significant area – How do you measure eyewitness accuracy? – Confidence is not a good measure – Speed of response is sometimes a good measure, but not in real-life, practical situations
Independent and Dependent Variables Types of Independent Variables Manipulated variable—True independent variable that is manipulated by the experimenter and can lead to random assignment Measured Variable—A variable that resembles a true independent variable bit is not; this variable is used to create discrete groups such that inclusion in groups is based on a characteristic of the participant Subject (Participant) Variable—Measured variable that resembles a true IV but is based on a pre-existing characteristic of the participant
Independent and Dependent Variables Types of Studies Using Discrete Groups for Comparison Experiment—A study in which participants are randomly assigned to groups Quasi-Experiment—A study that resembles a true experiment but involves comparison of groups that are not formed by random assignment of participants to groups Ex Post Facto Study—A study that resembles a true experiment but uses existing grouped data that did not involve random assignment of participants to groups
Independent and Dependent Variables Research Example of Measured IV – Question: Do depressed people have worse memories than non-depressed people? – Method: Assign people to groups based on pre- existing trait (i.e., are they depressed?) and test them for memory of positive words – Results: Depressed people remembered fewer positive words than non-depressed people did – Conclusion: Memory was poorer for depressed people, but because they came to the study depressed, there was no real manipulation of the IV, so you cannot draw a causal conclusion that depression hampers memory
Independent and Dependent Variables Research Example of a Manipulated IV – Question: Do suggestions affect memories? – Method: Randomly assign participants to groups and tell some participants that dreams indicate prior experience but do not tell that to other participants. – Results: Dream interpretations induce changes in memories of past events. – Conclusion: We can influence people’s memories by giving them erroneous information
Types of Independent and Dependent Variables Qualitative Variable—Variable based on qualitative differences (e.g., type of information given to participants) rather than on quantitative differences. Quantitative Variable—Variable based on quantitative differences like size, duration, amounts, etc.
Types of IVs and DVs Example of Study Using Qualitative IV Question: Do reports of hallucinatory dreams differ in different sleep stages? Method: Awaken people and get dream reports when they are in qualitatively different mental states. Result: Hallucinatory dreams change in different sleep states.
Types of IVs and DVs Example of Study Using Quantitative IV Question: Do different dosage levels of a drug affect performance of people with ADHD? Method: Randomly assign participants to conditions and assess performance on worksheets. Result: Increased dosages lead to improved performance only up to a point.
Types of IVs Types of Independent Variables Task Variable—An IV whose different conditions involve differences in a task that participants perform Instructional Variable—An IV whose different conditions involve different instructions given by the researcher to the participants Situational Variable—An IV whose different conditions involve different environments of contexts for different participants
Controversy: Studying Race Researchers often create quasi-experimental independent variables according to race of the participant. Is this an appropriate method? – Categorization to groups is often unclear in research and poorly done (e.g., based on a participant’s name) – Scientists increasingly believe that race is a social, not a biological, construct – Cultural factors as a “cause” of behavior may be more significant than biological factors – Social conditions may influence behaviors greatly – Research reports often do not report the race/ethnicity of the investigator, a possible source of biosocial effects
Controversy: Studying Depression Experimentally Are experiments on depression ethical? – Can an experimenter ethically induce depression? – Is it ethical to depart from effective treatments to study a person with depression? – Can you realistically induce depression in a nondepressed sample? Researchers have developed techniques to induce short-term, reversible states resembling very mild depression Experiments on depression can be safe and effective.
Comparing Two Groups Independent Groups Designs—Sometimes it is useful to create two separate groups with different people in each group. Repeated Measures Designs—Sometimes it is effective and efficient to test the same people in two conditions, so you need only half as many people as in independent groups designs.
Comparing Two Groups Generalizing Research Results – If we study college students in an experiment, can we generalize our results to other groups? If we study rats, fish, and pigeons, can we generalize the results to people? – When female fish saw male fish in the presence of other female fish, that male fish became more attractive as evidenced by the female’s interest. – Does that behavior pattern hold for women seeing a man in the presence of other women? The answer seems to be yes.
Comparing Multiple Groups Sometimes two groups are not enough to give us the answers we are looking for Researchers use multiple group designs
Comparing Multiple Groups Example of a Multiple-Group Design Question: Do people rate jokes differently if they expect the jokes to be funny or not funny? Method: Randomly assign participants to groups who expect funny jokes, unfunny jokes, or who have no particular expectations. Have participants rate the jokes Results: Expectations affected ratings
Data Analysis Experiments with Two Groups – Student’s t test for independent groups or Student’s t test for repeated measures groups Experiments with Multiple Groups Analysis of Variance (ANOVA) – Planned comparisons: Comparisons between groups in a multiple-group study; comparisons are planned before doing the data analysis – Post hoc comparisons: Comparisons between groups in a multiple-group study; comparisons are not determined before the ANOVA Note: ANOVA can be used with two groups, but typically is not if a study involves only one IV with two groups