Chapter 2: The Research Enterprise in PsychologyPart 1

AP Psychology 2014-2015

The Scientific Approach:A Search for Laws•Basic assumption: events are governed by

some lawful order•Goals:

1. Measurement and description2. Understanding and prediction3. Application and control

Figure 2.1 Theory construction

Figure 2.2 Flowchart of steps in a scientific

investigation

The Scientific Method: Terminology

•Operational definitions are used to clarify precisely what is meant by each variable

•Participants or subjects are the organisms whose behavior is systematically observed in a study

•Data collection techniques allow for empirical observation and measurement

•Statistics are used to analyze data and decide whether hypotheses were supported

Table 2.1 Key Data Collection Techniques in Psychology

The Scientific Method: Terminology•Findings are shared through reports at

scientific meetings and in scientific journals – periodicals that publish technical and scholarly material▫Advantages of the scientific method:

Clarity of communication and relative intolerance of error

•Research methods: General strategies for conducting scientific studies

Peer Review of Scientific Articles

• The process of publishing scientific studies allows other experts to evaluate and critique new research findings.

• They carefully evaluate each study’s methods, statistical analyses, and conclusions, as well as its contribution to knowledge and theory.

• The purpose of the peer review process is to ensure that journals publish reliable findings based on high-quality research.

Figure 2.4 The peer review process for

journal submissions.

Experimental Research: Looking for Causes

•Experiment = manipulation of one variable under controlled conditions so that resulting changes in another variable can be observed▫Detection of cause-and-effect relationships

•Independent variable (IV) = variable manipulated

•Dependent variable (DV) = variable affected by manipulation ▫How does X affect Y? ▫X = Independent Variable, and Y =

Dependent Variable

Operational Definition

•Used to quantify and clarify what is meant by each variable

•Used to be able to measure IV and DV•Example: Studying helps students

succeed in school.▫Independent Variable—studying▫Dependent Variable—success in school▫How do we measure or test what the IV and

DV are? Operational Def of IV: # of hours Operational Def of DV: grade on test

Experimental and Control Groups:The Logic of the Scientific Method

•Experimental group•Control group

▫Random assignment▫Manipulate independent variable for one group

only ▫Resulting differences in the two groups must be

due to the independent variable•Extraneous and confounding variables•Placebo effect• Video: Strange Powers of the Placebo Effect

Extraneous/Confounding Variables• Extraneous: Any variables other than the

independent variable that seem likely to influence the dependent variable

• Confounding: When two variables are linked together in a way that makes it difficult to sort out their independent effects

• Confounding variables are TYPES of extraneous variables

Extraneous Variables

Variables that affect the DV and are linked to the IV. •When extraneous variables are recognized during the design stage of the experiment, researchers use techniques to turn them into controlled variables. •If extraneous variables go unrecognized, they become confounded variables.

Confounded experiments• If an experiment has a third variable that changes

as the IV changes, the logic of the experiment is compromised. Any change in the DV that accompanies a change in the IV might be due to this third variable rather than the IV. If a third variable in an experiment is linked with the IV, the experiment is said to be confounded.

• Confounded variables are unfortunate. Although saying that they ruin an experiment is too strong, confounded variables do keep interpretations from being straightforward statements about the relationship between the IV and the DV. When a confounded variable could have been removed from an experiment but was not, the expression, CONFOUND IT! is appropriate.

For example…

• To study the effects of medication to treat depression while also undergoing counseling….

• You randomly assign people diagnosed as depressed into control and experimental groups. The control group is given placebo pills by Nurse A and talks to Counselor A for one hour every week.

• The experimental group is given your test pills by Nurse A but sees Counselor B for one hour every week. You find that the experimental group feels better at the end of the study.

• Unfortunately, you're study is not valid because the two groups saw different counselors. We can't say that it wasn't the counselor that made the subjects better, so your study is confounded.

• The differing techniques of the counselors are extraneous variables.

Controlled Variables

•When a potentially confounded variable is controlled, the logic of an experiment remains intact.

Nuisance Variables

•Another type of extraneous variable…•Characteristics of the participants or the

situation that makes the effects of the IV difficult to see

•Noise, uncomfortable temperatures, differences in IQ,

Terms Definition

Dependent variable (DV)

The behavior or outcome that is measured. It is expected to change as a result of changes in the IV

Independent variable (IV)

Variable with two or more levels chosen by the researcher. Changes in the IV are expected to be related to changes in the DV.

Confounded variable Variable that changes concurrently with the IV. The DV is affected by both the IV and the confounded variable.

Controlled variable Variable that changes concurrently with the IV, but whose effects can be distinguished from those of the IV.

Extraneous variable General term for a variable that changes concurrently with the IV.

Nuisance variable Variable that causes DV scores to be more variable

Experimental Designs: Variations

•Expose a single group to two different conditions▫Reduces extraneous variables▫When subjects serve as their own control

group, the experiment is said to use a within-subjects design

▫When two or more independent groups of subjects are exposed to a manipulation of an independent variable, the experiment is said to use a between-subjects design

Experiment QuestionWill Johnny get more phone numbers from girls if he wears Axe Body Spray?

Independent Variable

Axe Body Spray

Operational Definition of the Independent Variable

Before approaching the girls, Johnny will spray the Harmony scented Axe body spray evenly across his body for three seconds.

Dependent Variable

The quantity of phone numbers Johnny acquires

Operational Definition of the Dependent Variable

The number of phone numbers, Twitter addresses, email addresses, or Kik usernames that Johnny acquires.

Control Condition (Group)

Johnny wearing NO Axe body spray

Experimental Condition (Group)

Johnny wearing Axe body spray

Potential Extraneous Variables

Johnny’s personality, physical appearance, body odor, intelligence;The personal preferences of the girls he talks to

How we will prevent confounding variables

Johnny will be given a standard dialogue to use & outfit to wear.The girls will be pre-screened.

Experiment Summary Johnny will ask 10 girls for their phone numbers while wearing no Axe body spray. Then, he will ask 10 other girls for their phone numbers while wearing Axe body spray.

Experimental Designs: Variations

•Manipulate more than one independent variable▫Allows for study of interactions between variables▫Ex: study the effects of having the radio on when

people work on an assembly line…you’d collect data from the same group of workers twice, once with the radio on and once with it off.

•Use more than one dependent variable▫Obtains a more complete picture of effect of the

independent variable▫Ex: measure not only number of pieces workers

finish when the radio is allowed to be on while they work, but also worker satisfaction, absenteeism, and attitude.

Figure 2.6 The basic elements of an experiment

Population vs. Sample• Population: everyone of interest to whom a

study can be applied• Sample: a portion of the population that is

part of the study• Random sample: each item or member of the

population has an equal chance of being selected

• Representative sample: A small group whose characteristics accurately reflect those of the larger population from which it is drawn

Advantages and Disadvantages of Experimental Research

•Strengths: ▫conclusions about cause-and-effect can be

drawn•Weaknesses:

▫artificial nature of experiments▫ethical and practical issues

Biases•Hindsight Bias: “I knew it all along”

phenomenon•After learning the outcome of an event,

many people believe they could have predicted that very outcome.

•Ex: 9/11•Ex: dot.com stocks plummeting

Confirmation Bias• Searching for or interpreting new information

in a way that confirms your beliefs• Ex: A teacher looking for ways that girls have

scored better than boys because she thinks that girls are better.

• Ex: A Republican who only looks for information that confirms what he/she believes.

• Ex: An Obama fan who only looks for the good he has done & ignores the bad.

Overconfidence

•Sometimes we think we know more than we actually know.

•Study on anagrams: People said it would take about 10 seconds, yet on average they took about 3 minutes (Goranson, 1978).

Sampling Bias

•Some members of a population are more likely to be included in a study than others

•Dewey/Truman 1948 Presidential elections:▫Chicago Tribune: Dewey defeats Truman▫Survey of voters—telephone survey

Descriptive/Correlational Methods:Looking for Relationships

•Methods used when a researcher cannot manipulate the variables under study▫Naturalistic observation▫Case studies▫Surveys

•Allows researchers to describe patterns of behavior and discover links or associations between variables but cannot imply causation

• SNL census clip

Statistics and Research:Drawing Conclusions

•Statistics – using mathematics to organize, summarize, and interpret numerical data▫Descriptive statistics: organizing and

summarizing data▫Inferential statistics: interpreting data

and drawing conclusions

Descriptive Statistics:Measures of Central Tendency

• Measures of central tendency = typical or average score in a distribution

• Mean: arithmetic average of scores• Median: score falling in the exact center• Mode: most frequently occurring score

▫ Which most accurately depicts the typical?

Figure 2.11 Measures of central tendency

Descriptive Statistics: Variability

•Variability = how much scores vary from each other and from the mean▫Standard deviation = numerical depiction

of variability High variability in data set = high standard

deviation Low variability in data set = low standard

deviation

Figure 2.12 Variability and the standard deviation

Descriptive Statistics: Correlation

• When two variables are related to each other, they are correlated.

• Correlation = numerical index of degree of relationship▫ Correlation expressed as a number between 0 and

1▫ Can be positive or negative▫ Numbers closer to 1 (+ or -) indicate stronger

relationship

Correlation

Correlation Coefficient is a statistical measure of the relationship between two

variables.

When one trait or behavior accompanies another, we say the two correlate.

Correlation coefficient

Indicates directionof relationship

(positive or negative)

Indicates strengthof relationship(0.00 to 1.00)

r = 0.37+

Figure 2.13 Positive and negative correlation

Figure 2.14 Interpreting correlation coefficients

Perfect positivecorrelation (+1.00)

Scatterplot is a graph comprised of points that are generated by values of two variables. The slope

of the points depicts the direction, while the amount of scatter depicts the strength of the

relationship.

Scatterplots

No relationship (0.00)Perfect negativecorrelation (-1.00)

The Scatterplot on the left shows a negative correlation, while the one on the right shows no relationship between

the two variables.

Scatterplots

DataData showing height and temperament in people.

ScatterplotThe Scatterplot below shows the relationship

between height and temperament in people. There is a moderate positive correlation of +0.63.

Correlation:Prediction, Not Causation

• Higher correlation coefficients = increased ability to predict one variable based on the other▫ SAT/ACT scores moderately correlated with first year

college GPA

• 2 variables may be highly correlated, but not causally related▫ Foot size and vocabulary positively correlated▫ Do larger feet cause larger vocabularies?▫ The third variable problem

or

Correlation and CausationCorrelation does not mean causation!

Figure 2.15 Three possible causal relationships between correlated variables

Inferential Statistics:Interpreting Data/Drawing Conclusions

• Hypothesis testing: do observed findings support the hypotheses? ▫ Are findings real or due to chance?

• Statistical significance = when the probability that the observed findings are due to chance is very low [ P ≤ .05 ]▫ Very low = less than 5 chances in 100/ .05 level

Evaluating Research:Methodological Pitfalls

• Sampling bias • Placebo effects • Distortions in self-report data:

▫ Social desirability bias ▫ Response set a tendency to respond to questions in

a particular way (agree with everything, etc.).

• Experimenter bias ▫ the double-blind solution

• Replication—repeating an experiment/study that someone else has already done

• Meta-analysis--combining results from different studies to find patterns among study results

Figure 2.16 The relationship between the population and the sample

Ethics in Psychological Research:Do the Ends Justify the Means?

•The question of deception•The question of animal research

▫Controversy among psychologists and the public

•Ethical standards for research: the American Psychological Association▫Ensures both human and animal subjects

are treated with dignity

Figure 2.17 Ethics in research

The Internet and Psychological Research

Internet-mediated research refers to studies in which data collection occurs over the web.

Possible Advantages Samples that are much larger and much

more diverse than the samples typically used in laboratory research

Have the potential to yield more diverse and representative samples

The Internet and Psychological Research

•Potential Disadvantages▫Sampling bias resulting from self-

selection may be a more troublesome issue in Internet-mediated research Web users tend to be younger, brighter,

and more affluent than nonusers▫Data are collected under far less

controlled conditions than in traditional studies