Chapter 2The Research Enterprise in Psychology

Basic assumption: events are governed by some lawful orderGoals:

Measurement and descriptionUnderstanding and predictionApplication and control

The Scientific Approach: A Search for Laws

Operational definitions are used to clarify what variables mean

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

Findings are shared through reports at scientific meetings and in scientific journals

Research methods: general strategies for conducting scientific studies

Tools of the Trade: Definitions, Data, Journals, and Methods

Figure 2.1Theory construction. A good theory will generate a host of testable hypotheses. In a typical study, only one or a few of these hypotheses can be evaluated. If the evidence supports the hypotheses, our confidence in the theory they were derived from generally grows. If the hypotheses are not supported, confidence in the theory decreases and revisions to the theory may be made to accommodate the new findings. If the hypotheses generated by a theory consistently fail to garner empirical support, the theory may be discarded altogether. Thus, theory construction and testing is a gradual process.

Figure 2.2

Flowchart of steps in a scientific investigation. As illustrated in a study by Cole et al. (1996), a scientific investigation consists of a sequence of carefully planned steps, beginning with the formulation of a testable hypothesis and ending with the publication of the study, if its results are worthy of examination by other researchers.

Experiment = manipulation of one variable under controlled conditions so that resulting changes in another variable can be observedDetection 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

Experimental Research: Basics

Experimental group – subjects who receive some special treatment in regard to the independent variable

Control group – similar subjects who do not receive the special treatment Logic:

Two groups alike in all respects (random assignment)

Manipulate independent variable for one group only

Resulting differences in the two groups must be due to the independent variable

Experimental and Control Groups: The Logic of the Scientific Method

Expose a single group to two different conditions Reduces extraneous variables

Manipulate more than one independent variable Allows for study of interactions between variables

Use more than one dependent variable Obtain a more complete picture of effect of IV

Experimental Designs: Variations

Figure 2.6Manipulation of two independent variables in an experiment. As this example shows, when two independent variables are manipulated in a single experiment, the researcher has to compare four groups of subjects (or conditions) instead of the usual two. The main advantage of this procedure is that it allows an experimenter to see whether two variables interact.

Strength:conclusions about cause-and-effect

can be drawn Weaknesses:

artificial nature of experimentsethical and practical issues

Strengths and Weaknesses of Experimental Research

Methods used when a researcher cannot manipulate the variables under studyNaturalistic observationCase studiesSurveys

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

Descriptive/Correlational Methods: Looking for Links

Figure 2.10Comparison of major research methods. This chart pulls together a great deal of information on key research methods in psychology and gives a simple example of how each method might be applied in research on aggression. As you can see, the various research methods each have strengths and weaknesses.

Statistics – using mathematics to organize, summarize,

and interpret numerical dataDescriptive statistics:

organizing and summarizing dataInferential statistics:

interpreting data and drawing conclusions

Statistics and Research: Drawing Conclusions

Measures of central tendency = typical or average score in a distributionMean: arithmetic average of scoresMedian: score falling in the exact

centerMode: most frequently occurring

score Which most accurately depicts the

typical?

Descriptive Statistics: Measures of Central Tendency

Figure 2.11Measures of central tendency. The three measures of central tendency usually converge, but that is not always the case, as these data illustrate. Which measure is most useful depends on the nature of the data. Generally, the mean is the best index of central tendency, but in this instance the median is more informative.

Variability = how much scores vary from each other and from the meanStandard deviation = numerical

depiction of variabilityHigh variability in data set = high

standard deviationLow variability in data set = low

standard deviation

Descriptive Statistics: Variability

When two variables are related to each other, they are correlated.Correlation = numerical index of degree of

relationshipCorrelation expressed as a number

between 0 and 1Can be positive or negative

Numbers closer to 1 (+ or -) indicate stronger relationship

Descriptive Statistics: Correlation

Figure 2.13Positive and negative correlation. Notice that the terms positive and negative refer to the direction of the relationship between two variables, not to its strength. Variables are positively correlated if they tend to increase and decrease together and are negatively correlated if one tends to increase when the other decreases.

Figure 2.14Interpreting correlation coefficients. The magnitude of a correlation coefficient indicates the strength of the relationship between two variables. The sign (plus or minus) indicates whether the correlation is positive or negative. The closer the coefficient comes to +1.00 or –1.00, the stronger the relationship between the variables.

Figure 2.15Three possible causal relations between correlated variables. If variables X and Y are correlated, does X cause Y, does Y cause X, or does some hidden third variable, Z, account for the changes in both X and Y? As the relationship between smoking and depression illustrates, a correlation alone does not provide the answer. We will encounter this problem of interpreting the meaning of correlations frequently in this text.

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 relatedFoot size and vocabulary positively

correlatedDo larger feet cause larger

vocabularies?The third variable problem

Correlation: Prediction , Not Causation

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

Inferential Statistics: Interpreting Data and Drawing Conclusions

Sampling bias Placebo effects Distortions in self-report data:

Social desirability bias Response set

Experimenter bias and the double-blind solution

Evaluating Research: Watch for Methodological Pitfalls

The question of deception The question of animal research

Controversy among psychologists and the public Ethical standards for research: the American

Psychological AssociationEnsures both human and animal subjects are treated

with dignity

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

Figure 2.17Ethics in research. Key ethical principles in psychological research, as set forth by the American Psychological Association (1992), are summarized here. These principles are meant to ensure the welfare of both human and animal subjects.