Module 3

Research Strategies:

How Psychologists Ask and

Answer Questions

Can a 4 year old keep themselves from eating a marshmallow now,

If they are told they will get two later?

Video

Goals

Y Psychology: Scientific Study of Behavior

and Mental Processes

• Describe Behavior• Predict Behavior

• Explain Behavior• Control Behavior

Psychologists must be skeptical

and think critically

What is the evidence?

How was it collected?

Psychology is Empirical

Knowledge acquired through observation

Like all verdicts, the value and validity of the evidence must to examined.

Studies provide EVIDENCE to support or refute a theory.

Studies NEVER provide PROOF.

Like all verdicts,

the value and validity

of the evidence must

to examined.

Proof

General Principles

(Theory)

Empirical Predictions

Evidence Hypothesis

Observations

(data)

Advantage: Self correcting cycle.

Develop

theory

Caffeine improves people’s study skills

Scientific Method in Psychology

Refine

theoryDo the data support the theory?

Revise the theory to better fit the data.

Test

hypothesisRecord amount of caffeine consumed

and GPA for each student in the study.

Form

hypothesisStudents who drink 2 or more caffeine

beverages per day have higher GPAs

General Questions to Ask About a Study

1. Identify the variables!Variable: Anything that takes on different

values, at different times, places,

or in different individuals.

All studies have variables. They are the

constructs (qualities) we measure (e.g.,

intelligence, personality, or reaction

times).

You need to ask how the variables are defined?

Is the measure Valid? (Does it measure what it

claims to? Is the measure meaningful? Useful?)

Operational Definitions - Detailed descriptions

of measurement criterion.

How was ability to delay gratification (self

control, self discipline) operationally defined in

the Marshmallow Study?

2. Is the measuring device reliable?

- will the same value be obtained

- by different researcher

- at different times

Statements of precise operational definitions

allow scientists to Replicate studies.

Replications allow us to determine if the

results of a study are reliable.

Concept Check

1.What variable/construct measured in this study?

2. How is this variable operationally defined?

3. Is this a valid way of measuring this construct?

4. Is it a reliable way of measuring the construct?

5. Do the results support the conclusions made by the researcher?

SampleCollection of Ss used in a study

PopulationLarger collection of peopleabout which we wantto generalize

Sampling BiasWhen the sample isnot representative ofthe larger population

Sample

Population

2. You need to ask who is in the study?

If sample is restricted or biased this

limits the generalizability.

Volunteers?

Convenience Samples (University

Students)?

Small numbers of subjects can be used

to estimate the behavior of a larger

group as long as the sample is not

biased.

Representative Samples - matched

demographics.

Random Samples - eliminates bias.

Replications to Test Generalizability

to other Populations and Times

Often studies are done of specific populations

and researchers may want to know if you

would get similar results with other

populations. So they replicate the study with

samples from other populations.

e.g., Marshmallow Study was replicated with

Children in Columbia. Would we get same

results if we replicated the study today?

Types of Research

1) Descriptive: No Hypothesis

2) Relational Studies: (Circumstantial Evidence)

3) Experiments - evidence of cause and effect.

Remember: None of these are Proof.

Descriptive Studies

1) Case Studies

Detailed description of one person’s behavior

Useful for Rare Cases (e.g., Serial Killers,

or Rare Disorders).

• Concerns

Experimental Bias

Subject Bias

Generalizability

2) Naturalistic Observation

Studies

- real world settings

Concerns

- defining variables

- sampling (who, where and when)

- Experimenter Bias

- Observation can change behavior

3) Surveys

Ask People about behaviors or attitudes

Main Advantage: Can survey large numbers.

Concerns

Biased Samples

4 out of 5 dentists recommend brand X.

Generalizability

Subject Bias

Wording and method effects results

Class Survey.

Reasons for taking Class

Interesting 78% 93% 41%

Gen Ed Requirement

(need the credits) 15% 97% 83%

Learn about people 24% 44% 15%

Fun or Amusing 5% 42% 7%

Liked in High School 23% 24% 17%

Considering as Major 0% 3% 0%

Useful for career 3% 42% 18%

Understand Self 0% 14% 3%

Recommended to me 11% 5% 3%

Better than other options 3% 0% 0%

Cards All Top 2

5 Hour Energy Video

Relational Studies: what variables tend to go

together in predictable ways.

Correlations

Two variables measured on same person.

Correlation statistic ( r ). Ranges from -1 to +1

Positive - change in same direction.

High on one variable predicts high on the other.

Negative - change in opposite directions

Low on one variable predicts high on the other.

Absolute Value of r.

Strength of the relationship.

r = +1 or r = -1 perfect prediction.

r = 0 no ability to predict.

The closer to +1 or -1 the stronger the relationship

The closer to 0 the weaker the relationship

Correlations

Do young hockey players

take more penalties than

old hockey players?

r - statistical relationship

twixt 2 variables (age &

penalties)Penalty Minutes

Age

(-) r

Concept Check

Predict the correlation between these variables

(High, Medium or Low? Negative or Positive)

Weight and Height

IQ and shoe size

SAT scores and Grades in College

Miles you have drive since a fill-up and amount of gas

in your tank.

Number of Storks and Birthrate in a town

Correlation CausationSeveral Interpretations

A could cause B

B could cause A

C could be causing both A and B

Warning: People often try to use correlations as evidence

of cause. This is wrong.

True Experiments

Independent Variable (IV) - Variable that is

manipulated by Researcher. (Cause)

Dependant Variable (DV)- Measure of the

effect of manipulating the IV

•Purpose:

To see if changes in the IV cause changes in

the DV.

True Experiments

- objective measure

- a difference is produced (manipulated)

- all other variables held constant

If these three requirements are met, what

can we conclude about our results?

Cause Effect

Light Growth

When we conduct Experiments with

People we have an Experimental Group

and a Control Group. The two groups are

treated exactly the same except for the IV.

The level of the IV is under the control of

the experimenter (I.e., any person in the

study could be assigned to either the

experimental or the control group.)

Some studies compare different

groups of people to each other.

Random Assignment ensures that

there is no systematic reason why the

two groups should differ. Any

differences are due to chance.

Confound – anything other than the

manipulated variable that is different

between two conditions.

Serves as an alternative explanation of the

cause of differences between conditions.

Natural Experiments - look like experiments,

but they are confounded.

-Variable is not manipulated by experimenter.

e.g., comparisons of pre-existing or self-

selecting groups.

Males vs. Females

People who use Match.com vs. those who do

not.

If Males score better on Math tests than

Females can I say being Male causes better

math scores?

Other explanations?

Other Biases (Can occur in any type of study)

Experimenter Bias

- blind Observers

Expectancy Effects

- e.g., placebo effect

Double blind procedures.

- both observer and subjects are blind to expected

results.

Statistics

- allow us to describe findings

Measures of Central Tendency

Mean – arithmetic average

Medium – Midpoint

Mode – Most Frequent

Measures of Variation

How much variation is there is the measures?

Range – lowest through highest.

Standard Deviation – Average distance of the

scores from the Mean. Larger the Standard

Deviation the more variable the scores in the

distribution are.

IE(DS) 43

Symmetrical Distribution

0

2

4

6

8

1 2 3 4 5 6 7 8 9 10

Variable Measured

Fre

qu

en

cy

Shape of Distributions

Symmetrical - scores evenly

distributed around the mid-

point of the distribution.

Skewed Positivily

0

1

2

3

4

5

6

1 2 3 4 5 6 7 8 9 10

Variable Measured

Fre

qu

en

cy

Skewed Distributions - scores pile up on one end of the curve.Skewed Negitively

0

1

2

3

4

5

6

1 2 3 4 5 6 7 8 9 10

Variable Measured

Fre

qu

en

cy

IE(DS) 44

In a symmetrical, unimodal, distribution the

Mode, Median and Mean will all be the same.

When the distribution is skewed, or contains

some deviant scores, these three measures can

be very different.

IE(DS) 45

Normal Curve

Bell shaped curve describes

many variables in the

natural world.

Allows us to estimate the

probability of scores at any

place in the distribution.

Tests of Statistical Significance

If a result is statistically significant, the

difference between conditions is unlikely to

be due to chance alone.

Statistical Significant Important

Better question: How big is the

difference?