Midterm Flashcards
Four Goals of Scientific Research
To Describe Behavior
To Predict Behavior
To Determine Cause of Behavior
To Understand or Explain Behavior
Producer vs Consumer
Producer - Take part in research process (studying, observing, conducting experiments, surveying)
Professor, lab volunteer, research scientist, etc.
Consumer - Read about research and apply to jobs or everyday lives
Therapists, counselors, teachers, etc.
Sources of Research Ideas
Common assumptions Observation of the world around us Practical problems Theories Past research
Source of information: Your Experience
No comparison group
Confounded - can not be sure what cause is
Only one point in overall pattern
Source of information: Your intuition
Cognitive Biases - Swayed by a good story, Availability Heuristic, Present/Present Bias
Motivation Biases - Focus on evidence that supports our beliefs, Ask biased questions, Biased about being biased
Research is Probabilistic
Scientific conclusions are based on patterns that emerge with multiple tests and comparison
Findings are not expected to explain all of the cases all of the time - only a certain portion of the possible cases
The Intuitive Thinker vs the Scientific Reasoner
Intuitive thinking leads to mistakes
To counteract biases we need to adopt the empirical mindset of a researcher:
Base beliefs on systematic information
Strive to interpret data in an objective way
Trusting Authorities on the Subject
Before taking advice of authorities ask yourself the source of their ideas:
Could be based on research but not all research is equally reliable
Could be based on experience
Could be based on intuition
Could be biased
Anatomy of a Research Article: Abstract
Summary of entire research report/proposal
150-250 words
Includes: Hypothesis, procedure, broad pattern of results
Anatomy of a Research Article: Introduction
Outlines the problems being investigated
Past research and theories relevant to the problems
Formal hypothesis or specific expectations are introduced and connected to past research
Anatomy of a Research Article: Method
Subsections: Participants, materials, procedures, apparatus
Overview of design
Characteristics of participants
Procedure
Equipment and materials
Anatomy of a Research Article: Results
How data will be examined
Findings presented in three ways:
Description in narrative form
Description in statistical language
Material in table or graphs
Anatomy of a Research Article: Discussion
Review of research from various perspectives
Present methodological weaknesses or strengths
Explain how the results compare with past results
Includes suggestions for practical applications
Includes suggestions for future research on topic
Basic vs Applied Research
Basic - attempts to answer fundamental questions about the nature of behavior with the goal of enhancing general body of knowledge
Applied - addresses issues in which there are practical problems and potential solutions, often guided by basic research
Measured vs Manipulated Variables
Measured - levels are observed and recorded
Manipulated - levels are changed and controlled by researcher
Independent vs Dependent Variables
Independent - levels are changed and controlled to test effect on dependent variable
Dependent - levels are tested and measured and suspected to be affected by the independent variable
Operational Definition
Defining a conceptual variable at the theoretical level
Clear, concise, detailed definition of a measure
Operationalize
Turn a concept of interest into a measured or manipulated variable
Types of Measures
Self-report
Observational
Physiological
Empiricism
Conclusions are based on systematic observation
Characteristics of Scientific Approach
Make systematic observations and report them accurately
Engage in Theory-Building - development, testing, and refining of theories
Maintain an open system where falsifiable ideas are exchanged, debated, and challenged
Submit findings for peer-review
Theory
A set of statements that describes the general principles about how variables related to one another
Frequency Claim
Describe a particular rate or degree of a single variable
Focus on only ONE variable
Variable is measured (not manipulated)
Ex. 1 in 4 children enjoy potatoes
Association Claim
Argue that one level of a variable is associated with a particular level of another variable
Involves at least TWO measured variables (interval or ratio)
Correlated - as one variable changed the other tends to change also
Positive Association
High levels go with high levels, low levels go with low levels
Ex. High score in badminton associated with high amount of practice
Negative Association
High levels go with low levels, and low levels go with high levels
Ex. High scores on test associated with low amount of distractions during studying
Zero Association
No relationship among variables
Causal Claims
Argues that one variable is responsible for changing another variable
Criteria for Causal Claim
Covariation - must establish that one variable causes another
Temporal Precedence - must establish the causal variable happened before the effect variable
Internal Validity - Must establish that no other explanation exists for the relationship
Construct Validity
How well the variables in a study are measured or manipulated
Extent to which the operational variables used in a study are a good approximation of the conceptual variables
External Validity
The extent to which the results of a study generalize to some larger population as well as to other times or situations
Statistical Validity
The strength of an effect and its statistical significance (the probability that the result could have been obtained by chance if there really is no effect)
Extent to which a study minimizes the probabilities of two errors:
Type I - False-Positive: Concluding that there is an effect when there is none
Type II - Miss: Concluding that there is no effect when there is one
Internal Validity
The extent to which a confound is not responsible for the observed effect
The relationship between one variable (A) and another (B) and the extent to which (A) rather than some other variable (C) is responsible for the effect on (B)
Validity
Appropriateness of a conclusion
Valid claim - reasonable, accurate, and justifiable
Frequency Claim Validity
Construct Validity - How well was the variable measured
Statistical Validity- How well do the numbers support the claim
External Validity - Can we generalize from the sample to the population
Margin of Error
Statistical figure which indicates where the true value in the population probably lies
Association Claim Validity
Construct Validity of each variable - How well each were measured and constructed
Statistical Validity - How strong is the association, is it statistical significant, were mistaken conclusions avoided
External Validity - Can we generalize to the population as well as other contexts, times, or places
Statistical Significance
Likelihood that a relationship between variables is caused by something other than random chance
Statistical Significance: Mistaken Conclusion Errors
Error Type I - False-Positive - assuming a relationship when there is none
Error Type II - False-Negative - (Miss) - assuming no relationship when there is one
Causal Claim Validity
Construct validity of both variables - how well were they measured or manipulated
Statistical Validity - How big is the difference is it statistically significant
Internal Validity - Are there other possible explanations
External Validity - To who or what can we generalize this effect
Types of claims and variables
Frequency - 1 nominal variable
Association - 2 interval or ratio variables
Causal - 1 manipulated, 1 interval or ration variable
