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## Intro to Research Chapter 3 Week 2 lecture

by: Kim Notetaker

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# Intro to Research Chapter 3 Week 2 lecture

Marketplace > Armstrong State University > > Intro to Research Chapter 3 Week 2 lecture
Kim Notetaker

GPA 3.4

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These notes are a summary of chapter 3. These notes pertain to our exam.
COURSE
Intro to Research Methods
PROF.
TYPE
Class Notes
PAGES
2
WORDS
CONCEPTS
PSYC, research, notes
KARMA
25 ?

## Popular in Department

This 2 page Class Notes was uploaded by Kim Notetaker on Friday September 30, 2016. The Class Notes belongs to at Armstrong State University taught by in Fall 2016. Since its upload, it has received 7 views.

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Date Created: 09/30/16
Chapter 3 Variables  Variable: anything you can measure or manipulate.  Levels: the value of the variable in the study.  Constant: something in the study that you can change but will not change and it has only 1 level.  Measure Variable: a variable that is observed or recorded as it occurs naturally.  Manipulated Variable: the variable that the researcher controls and changes.  Dependent Variable: the outcome variable; always measured and never manipulated.  Independent Variable: the predictor variable; always manipulated but can be measured.  Conceptual Variable: this is an abstract concept or construct.  Conceptual definition: the precise definition or description of the construct. o An example of a construct can be love, and the conceptual definition would be that is profoundly tender, passionate affection towards others.  Operational Variable: the specific way a variable will be manipulated or measured. o This can also be called an operational definition or operationalization.  Validity: the appropriateness of the conclusion or the decision. o An example of this will be like a bouncer checking your i.d. to see if you are actually 21. The 4 Validity types  Construct Validity: how well did the researcher operationalize (use) each variable?  External Validity: how well do the results generalize or represent the people outside the study?  Internal Validity: in the experiment; how sure are you that the change in the dependent variable is from the independent variable?  Statistical Validity: how well does the number data support the researcher’s conclusion? o The assessment depends on the nature of the claim.  Frequency claim: has a margin of error indicating validity and where the true value in the population is.  Association Claim: casual claims can be evaluated based on their strength and statistical significance.  Try to avoid errors when assessing the statistical validity.  Type 1 error: false alarm or a false positive; saying a relationship exist when one doesn’t. o An example would be telling someone that they are pregnant but they are not.  Type 2 error: false negative; saying that no relationship exists when one does. o An example would be telling someone that they are not pregnant and they are.  Try to avoid type 2 errors, but type 1 errors are tolerated more than type 2. 2

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