Chapter 4: Fundamental Research Issues Flashcards
What is a variable
Any event, situation, behavior, or individual characteristic that can take on different values or levels.
Classifying Variables (3 parts)
- Can it be Manipulated?
- How to Measurement it.
- How to Define it.
Manipulating Variables
Can it be manipulated? Or can it only be measured?
Example:
Participant Variables → canNOT be manipulated (ie: hight, gender, etc)
Independent Variables –> can be manipulated (ie: daily caffeine intake)
Measuring Variables
Scale of Measurement = NOIR
N – Nominal (category or name)
O – Ordinal (ranking)
I – Interval (numbers equally spaced)
R – Ratio (interval + meaningful zero)
- I + O (Interval + Ratio) = “Scale” variables
Measuring Variables - Importance of Scales
Scales determine statistical analyses
Defining Variables
Importance: Must define variables so that…
a) They can be studied empirically
b) Scientists can communicate their ideas about concepts
How: Variables are defined via Operational Definitions
Operational Definition of Variables
The set of procedures used to measure or manipulate the variable.
- They set the boundary of what is studied and what one can/should claim.
- All evidence should be described using operational definitions
The adequacy of an operational definition of a variable is called Construct Validity
Importance of Wording
Avoid using “prove” and “proof”
Instead use words like: “Supports”, “Contradicts”, “indicates”
Relationships Between Variables with true numeric properties
- Positive-Linear Relationship — As one variable increases, so does the other
- Negative-Linear Relationship — As one variable increases, the other decrease
- Curvilinear Relationship — One variable may increase, but the other increases and decreases. (direction of relationship changes)
- No Relationship — Changes in one variable are not associated with changes in the one.
Correlation Coefficient
Measurement of how strongly two variables are related to each other.
Experimental Research Method
Description: Manipulation of an IV in a controlled condition and measurement of its effects of the DV
Setting: Controlled lab environment
Strengths: can examine cause & effect relationship between variables (IV & DV)
Weaknesses: Limited ability to generalize to real world behavior. Some variables cannot be manipulated, thus cannot be studied experimentally.
Non-Experimental Research Method
Description: Measurement of one or more variables through observation, survey, psychological tests, and more.
Setting: Real world setting (but sometimes in a lab environment)
Strengths: Gather detailed/descriptive date from real-world settings (usually). Enhanced Ecological Validity
Weaknesses: Many unrelated and/or third variables prevent determining cause-and effect claims.
Experimental vs Non Experimental - Test Prep Questions
Test Prep:
1. Describe the distinctions between experimental and non-experimental research methods.
- In what settings do the different approaches tend to take place?
- What are some key strengths of each approach?
- What are some major weaknesses of each approach?
Ecological Validity
How well a study’s results can be applied to real life
Internal Validity
How accurately the study’s evidence supports claims about causal relationships
