Ch. 2 Studying behavior scientifically

Ch. 2 Studying behavior scientifically

Scientific principles in psychology

• Curiosity, scepticism and
• open-mindedness are key scientific attitudes.
• The scientific process proceeds
• through several steps:
• 1. Asking questions based on some type of observation,
• 2. Formulating a tentative explanation and a testable hypothesis,
• 3. Conducting
• research to test the hypothesis,
• 4. Analysing the data and drawing a tentative
• conclusion,
• 5. Reporting one’s findings to the scientific community,
• 6.
• Building a theory and
• 7. Using the theory to generate new hypotheses, which are
• tested by more research.

Hindsight

• In everyday life we typically
• use hindsight to explain behavior.
• Hindsight is flawed because there are many
• possible explanations and no way to assess which is correct.
• Psychologists
• prefer to test their understanding through prediction, control and theory
• building.

Slide 4

• A good theory organizes known
• facts, gives rise to additional hypotheses that are testable, is supported by
• the findings of new research and is parsimonious.
• An operational definition
• defines a concept or variable in terms of the specific procedures used to
• produce or measure it.
• To measure behaviour,
• psychologists obtain people’s self-reports and reports from others who know the
• participants, directly observe behaviour, use unobtrusive measures, analyse
• archival data, administer psychological tests and measure physiological
• responses.

Ethical principles in research

• Psychological research follows
• extensive ethical guidelines. In human research, key issues are the use of
• informed consent, the participants’ right to privacy, potential risks to
• participants and the use of deception.
• Ethical guidelines require that
• animals be treated humanely and that the risks to which they are exposed be
• justified by the potential importance of the research. As in human research,
• before animal research can be conducted it must be reviewed and approved, often
• by ethics review boards that include non-scientists.
• Scientists have a
• responsibility to conduct themselves ethically both in the design and execution
• of their work as well as in the dissemination of their data. We as scientists
• have a responsibility to live up to the trust society puts in us. If we do not,
• we bring ourselves, science and psychology into disrepute.

Methods of research

• Descriptive research describes
• how organisms behave, particularly in natural settings. Case studies involve
• the detailed study of a person, group or event. They often suggest ideas for further
• research, but are a poor method for establishing cause-effect relations.
• Naturalistic observation
• gathers information about behaviour in real-life settings. It can yield rich
• descriptions of behaviour and allows the examination of relations between
• variables. Researchers must avoid influencing the participants that they
• observe.
• Surveys involve administering
• questionnaires or interviews to many people. Most surveys study a sample that
• is randomly drawn from the larger population in which the researcher is
• interested. Representative samples allow for reasonably accurate estimates of
• the opinions or behaviours of the entire population. Unrepresentative samples
• can lead to inaccurate estimates. Interviewer bias and bias in participants’
• self-reports can distort survey results.

Slide 7

• Correlational research measures
• the relation between naturally occurring variables. A positive correlation
• means that higher scores on one variable are associated with higher scores on a
• second variable. A negative correlation occurs when higher scores on one
• variable are associated with lower scores on a second variable.
• Causal conclusions cannot be
• drawn from correlational data. Variable X may cause Y, Y may cause X or some
• third variable (Z) may be the true cause of both X and Y. Nevertheless, if two
• variables are correlated, then knowing the scores of one variable will help
• predict the scores of the other.

Slide 8

• A well-designed experiment is
• the best way to examine cause-effect relations. Experiments have three
• essential characteristics: 1) one or more variables are manipulated, 2) their
• effects on other variables are measured, and 3) extraneous factors are
• eliminated or reduced so that cause-effect conclusions can be drawn.
• Manipulated variables are
• called independent variables. Dependent variables are measured, not
• manipulated. The independent variable is viewed as the cause, the dependent
• variable as the effect.
• The experimental group receives
• a treatment or an active level of the independent variable, whereas the control
• group does not.

Slide 9

• In some experiments different
• participants are randomly assigned to each condition. In other experiments the
• same participants are exposed to all the conditions, but the order in which the
• conditions are presented is counterbalanced.
• Researchers can study several
• causal factors within one experiment by simultaneously manipulating two or more
• independent variables. They asses the separate influence of each variable on
• behaviour and examine whether combinations of variables produce distinct
• effects.

Threats to the validity of research

• An experiment has high internal
• validity when it is designed well and permits clear casual conclusions.
• Confounding occurs when the
• independent variable becomes mixed up with an uncontrolled variable. This ruins
• internal validity because we can no longer tell which variable caused the
• changes in the dependent variable.

Slide 11

• Internal validity is weakened
• by: 1) demand characteristics, which are cues that tip off participants as to
• how they should behave; 2) placebo effects, in which the mere expectation of
• receiving a treatment produces a change in behaviour; and 3) experimenter
• expectancy effects, which are the subtle ways a researcher’s behaviour
• influences participants to behave in a manner consistent with the hypothesis
• being tested.
• The double-blind procedure
• prevents placebo effects and experimenter expectancy effects from biasing
• research results.
• External validity is the degree
• to which the findings of a study can be generalized to other populations,
• settings, and conditions. By replicating (repeating) a study under other circumstances,
• researchers can establish its external validity.

Analysing and interpreting data

• Statistics can be misleading if
• they are based on very few observations or are distorted by extreme scores.
• Understanding basic statistical concepts can help you be a smarter citizen and
• consumer.
• Descriptive statistics
• summarize the characteristics of a set data.
• Measures of central tendency
• identify the typical score in a distribution. The mode is the most frequent
• score. The median is the halfway point in a distribution of scores arranged in
• numerical order; half of the scores are above and half are below. The mean is
• the arithmetic average of the scores.

Slide 13

• Measures of variability assess
• whether scores are clustered together or spread out. The range is the difference
• between the highest and lowest scores. The standard deviation takes into
• account how much each score differs from the mean.
• Inferential statistics allow
• researchers to determine whether their findings reflect a chance occurrence.
• The term statistical significance means that it is very unlikely that a
• particular finding occurred by chance alone.
• Meta-analysis statistically
• combines the results of many studies that examine the same variables. It
• calculates the direction and strength of the overall relation between those
• variables.

Critical thinking in science and everyday life

• Critical thinking is an
• important life skill. We should also be open-minded to new ideas that are
• supported by solid evidence.
• In science and everyday life,
• critical thinking can prevent us from developing false impressions about how
• the world operates and from being duped in everyday life by unsubstantiated
• claims.
• When someone presents you with
• a claim, you should consider the quality of the evidence, whether there are other
• plausible explanations for the conclusions being drawn, and whether additional
• evidence is needed to reach a clearer conclusion. Then ask yourself whether the
• claim is the most reasonable conclusion to draw.