Good Theories & Basic Methodologies

Psych 231: Research Methods in Psychology

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Quiz 3 due date error: I’ve reset the due date on Quiz3 to Wednesday (9/10) to make up for accidentally having it close yesterday instead of today

Exam 1: One week from Wednesday

Properties of a good theory

Organizes, Explains, & Accounts for the data If there are data relevant to your theory, that your

theory can’t account for, then your theory is wrong• Either adapt the theory to account for the new data • Develop a new theory that incorporates the new data

The chicken or the egg?

Exclusive usage of one or the other can be problematic Typically good research programs use both

Theory

Data

Induction Deduction

“Data driven research”reasoning from the data to the general theory

“Theory driven research”reasoning from a general theory to the data

Properties of a good theory

Organizes, Explains, & Accounts for the data Testable/Falsifiable – can’t prove a theory, can

only reject it

“No amount of experimentation can ever prove me right; a single experiment

can prove me wrong.”

Omnipotent Theory

Beware theories that are so powerful/general/flexible that they can account for everything. These are not testable. Karl Popper claimed that Freudian theory isn’t falsifiable

• If display behavior that clearly has sexual or aggressive motivation, then it is taken as proof of the presence of the Id

• If such behavior isn’t displayed, then you have a “reaction formation” against it. So the Id is there, you just can’t see evidence of it.

So, as stated, the theory is too powerful and can’t be tested and so it isn’t useful

EXTINCTION OF THE DINOSAURS FULLY EXPLAINED

Another nice article on this

Properties of a good theory

Organizes, Explains, & Accounts for the data Testable/Falsifiable Generalizable

The theory should be broad enough to be of use, the more data that it can account for the better

The line between generalizability and falsifiability is a fuzzy one.

Properties of a good theory

Organizes, Explains, & Accounts for the data Testable/Falsifiable Generalizable Parsimony (Occam’s razor)

For two or more theories that can account for the same data, the simplest theory is the favored one

“Everything should be made as simple

as possible, but not any simpler.”

Properties of a good theory

Organizes, Explains, & Accounts for the data Testable/Falsifiable Generalizable Parsimony Makes predictions, generates new knowledge

Predictions about things that the theory wasn’t explicitly designed to account for

Conducting Research: An example

Claim: People perform best with 8 hours of sleep a night.

How might we go about trying to test this claim? What are the things (variables) of interest? What is the hypothesized relationship between these

variables? How should we test it (what methods)? Today’s focus

General research approaches

Descriptive Describing the current state of the individual variables

• Observational, Survey, Case studies

Correlational Investigating the relationship between two (or more)

variables

Experimental Investigating the cause-and-effect relationship between

two (or more) variables

Descriptive: Observational methods

Observational methods The researcher observes and systematically records

the behavior of individuals

• Naturalistic observation

• Participant observation

• Contrived observation

Descriptive: Observational methods

Naturalistic Observation: Observation and description of behaviors within a natural setting

Jane Goodall

Dian Fossey

Good for behaviors that don’t occur (as well) in more controlled settings

Often a first step in the research project

Can be difficult to do well

Descriptive: Observational methods

Participant Observation: The researcher engages in the same behaviors as those being observed May allow observation of behaviors not normally accessible

to outside observation Internal perspective from direct participation

• But could lead to loss of objectivity Potential for contamination by observer

Descriptive: Observational methods

Contrived Observation: The observer sets up the situation that is observed Observations of one or more specific variables made in a

precisely defined setting Much less global than naturalistic observations Often takes less time However, since it isn’t a natural setting, the behavior may be

changed

Descriptive: Observational methods

Advantages Complex patterns of

behavior in particular settings

Useful when little is known about the subject of study

May learn about something that never would have thought of looking at experimentally

Disadvantages Causality is a problem Threats to internal validity

because of lack of control• Every confound is a threat• Lots of alternative

explanations Directionality of the

relationship isn’t known Sometimes the results are not

reproducible

Descriptive: Survey methods

Widely used methodology More detail in Week 11

Can collect a lot of data Done correctly, can be a very difficult

method Doesn’t provide clear cause-effect patterns

Descriptive: Case Histories

This view has a number of disadvantages There may be poor generalizabilty There are typically a number of possible

confounds and alternative explanations

Intensive study of a single person, a very traditional method Typically an interesting (and often rare) case

Phineas Gage Sept 13, 1848 Explosion

propelled a railroad tamping rod through his brain

Correlational Methods

Measure two (or more) variables for each individual to see if the variables are related

Used for: Predictions Reliability and Validity Evaluating theories

Problems: Can’t make casual claims

Causal claims

We’d like to say:

variable X --causes--> variable Y

To be able to do this: There must be co-variation between the two variables The causal variable must come first

Directionality problem

• Happy people sleep well• Or is it that sleeping well when you’re happy?

Need to eliminate plausible alternative explanations Third variable problem

• Do Storks bring babies?• A study reported a strong positive correlation between

number of babies and stork sightings

Theory 1: Storks deliver babies

Theory 2: Underlying third variable

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are needed to see this picture.

The experimental method

Manipulating and controlling variables in laboratory experiments

Must have a comparison At least two groups (often more) that get compared One groups serves as a control for the other group

Variables Independent variable - the variable that is manipulated Dependent variable - the variable that is measured Control variables - held constant for all participants in the

experiment

The experimental method

Advantages Precise control

possible Precise measurement

possible Theory testing possible Can make causal

claims

Disadvantages Artificial situations

may restrict generalization to “real world”

Complex behaviors may be difficult to measure