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by: Madilynne Harbauer

PSYC_100_Notes_9_7_16.pdf PSYC 100

Madilynne Harbauer

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About this Document

Research methods part 2
Introduction to Psychology
Dr. Kimberly Vanderbilt
Class Notes
Psychology, Intro to Psychology, Researchmethods




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Popular in Psychology (PSYC)

This 2 page Class Notes was uploaded by Madilynne Harbauer on Friday September 23, 2016. The Class Notes belongs to PSYC 100 at California State University - San Marcos taught by Dr. Kimberly Vanderbilt in Fall 2016. Since its upload, it has received 4 views. For similar materials see Introduction to Psychology in Psychology (PSYC) at California State University - San Marcos.


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Date Created: 09/23/16
9/7/16 Research Methods: Part 2 - You can’t measure things as big as love or intelligence • We can turn it into a measured variable and that becomes your experimental definition of your conceptual variable - Has implications for conclusions you draw from results Population: Group you hope to learn something about Sample: Section of the population tested • The people that actually end up in your study Experimental group: Group(s) that received the manipulation Control group: Group that does not receive the manipulation Ex: Plants Plants —> receive fertilizer (experimental group) Plants —> don't receive fertilizer (control group) If you measured them both you would know if that helped growth Placebo:Afake testing condition, so people THINK they are getting a treatment, but really are not • this controls the placebo effect • Placebo effect: change due to subjects expectation Ex: taking “smart pills” —> thinking you're smart so you read —> reading might actually make you smarter (but it would be from reading, not taking the pill) Random assignment: Randomly assorting participants into groups • Makes sure that groups do not have pre-existing difference that could cause another effect • They need to be balanced and have no bias Independent variable: Thing that is manipulated Dependent variable: Thing that is measured Confound: anything other than the independent variable that causes a difference between the groups Eliminate as many other things as possible • • Make sure the independent variable is the only thing that matters Reliability: Consistency of measurement • Always give you the same result Ex:Aruler, you should get the same result from measuring every time Counter-Ex: Magic 8 ball, its different every time Validity: Extent to which whats measured is what was supposed to be measured • You have to use it for the right stuff or it wont make sense Ex: Ruler measures height or length, not weight Internal validity: Does your experiment show what you think it does (was it done “right?”) External validity: How well can you generalize your findings beyond your sample/experiment? • Does it apply to other people you didn't ask> Study designs: - Different studies are designed for different types of purposes • To find an answer to something Observational: Watching behavior, often in a real world setting • Does not manipulate anything • Records naturally occurring behavior • Includes naturalistic observations Correlational: examines the extent to which two variables are associated • Also does not manipulate anything • Observes how two variables are related in the world Ex: People who have good education, have a high salary • As x changes, how does y change - Correlation does not equal causation • Just because it’s related, doesn't mean one causes the other Experimental: Randomly assigns participants to different groups and manipulates an independent variable • Can make conclusions about the cause of the results Case-study: involves studying just one individual… a lot. • Sometimes there’s only one person that can give us that info • Have to be careful about external validity • Don’t usually like to focus on 1 person because we don't want to assume about other people Longitudinal study: Testing the same group of people repeatedly over a long period of time


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