the tendency to believe, after learning an outcome, that one would have foreseen it. (a.k.a. the I-knew-it-all-along phenomenon); learning the outcome of a study can make it seem like common sense.
we are routinely overconfident of our judgments, thanks partly to our bias to seek information that confirms them.
thinking that does not blindly accept arguments and conclusions. Rather, it examines assumptions, discerns hidden values, evaluates evidence, and assesses conclusions.
Critical Thinking Skills
willing to ask questions, analyze assumptions, examine the evidence, be cautious of emotional decisions, and tolerate uncertainty.
set of procedures used to gather, analyze, and interpret information in a way that reduces error and leads to dependable conclusions.
an explanation using an integrated set of principles that organizes observations and predicts behavior or events.
a testable prediction, often implied by a theory.
a statement of the procedures (operations) used to define research variables. For example, human intelligence may be operationally defined as what an intelligence test measures.
repeating the essence of a research study, usually with different participants in different situations, to see whether the basic finding extends to other participants and circumstances.
an observation technique in which one person is studied in depth in the hope of revealing universal principles. (cross-sectional).
a technique for ascertaining the self-reported attitudes or behaviors of people, usually by questioning a representative, random sample of them; wording effects - subtle influences in the sequence or phrasing of questions - can affect responses.
False Consensus Effect
the tendency to overestimate the extent to which others share our beliefs and behaviors.
all the cases in a group, from which samples may be drawn from a study.
a sample that fairly represents a population because each member has an equal chance of inclusion.
observing and recording behavior in naturally occurring situations without trying to manipulate and control the situation. Like other forms of description, naturalistic observation can't explain behaviors, but it can expand our understanding and lead to hypotheses that can be studied by other methods.
a measure of the extent to which two factors vary together, and thus of how well either factor predicts the other. A correlation can not be translated into cause and effect, it is only a relationship.
Correlation Coefficient (r)
the mathematical expression of the relationship, ranging from -1 to +1.
a graphed cluster of dots, each of which represents the values of two variables. The slope of the points suggests the direction of the relationship between the two variables. The amount of scatter suggests the strength of the correlation (little scatter indicates high correlation). (Also called a scattergram or scatter diagram.).
the perception of a relationship where none exists. Once we believe two things are related, we tend to notice and recall instances that confirm this belief.
a research method in which an investigator manipulates one or more factors (independent variables) to observe the effect on some behavior or mental process (the dependent variable). By random assignment of participants, the experimenter aims to control other relevant factors.
an experimental procedure in which both the research participants and the research staff are ignorant (blind) about whether the research participants have received the treatment or a placebo. Commonly used in drug-evaluation studies.
experimental results caused by expectations alone; any effect on behavior caused by the administration of an inert substance or condition, which is assumed to be an active agent.
the condition of an experiment that exposes participants to the treatment, that is, to one version of the independent variable.
the condition of an experiment that contrasts with the experimental condition and serves as a comparison for evaluation the effect of the treatment.
assigning participants to experimental and control conditions by chance, thus minimizing preexisting differences between those assigned to the different groups.
the experimental factor that is manipulated; the variable whose effect is being studied. It is the one that the researcher is testing as the possible cause of any changes that might occur in the other variable.
the outcome factor; the variable that may change in response to manipulations of the independent variable.
a researcher's expectations or preferences about the outcome of a study influence the results in a hoped-for direction.
subjects do not know whether they are in the experiment or control group.
allows researchers to organize, describe, and make meaningful judgments from data collected; provides researchers with information to judge whether a hypothesis should be accepted or rejected.
presents numbers that summarize and describe data in a practical, efficient manner.
used to determine whether the data supports or rejects a hypothesis; used to estimate the likelihood that a difference found in the research sample would also be found in the entire population.
Measures of Central Tendency
when researchers summarize data, they use a number to describe the central location with the distribution of scores in a sample. (mean, median, mode).
normal distribution - mean, median, mode are all the same value; positively skewed distribution - mode is lowest and mean is highest; negatively skewed distribution - mean is lowest and mode is highest.
the most frequently occurring score(s) in a distribution.
the arithmetic average of a distribution, obtained by adding the scores and then dividing by the number of scores.
the middle score in a distribution; half the scores are above it and half are below it.
Measures of Variation
statistics that tell you how closely distributed your scores are to some measure of central tendency. (range, standard deviation).
the difference between the lowest and the highest scores in a distribution.
a computed measure of how much scores vary around the mean score; average difference between scores and their mean. Low s.d. - the mean provides a good representation of the entire set for that variable. High s.d. - the mean is not a very good representation of all data for the variable.
mathematical methods used to determine whether the data supports or does not support the hypothesis. Most research is done on smaller samples so the data is not applicable to large populations; need to expand the research.
a statistical statement of how likely it is that an obtained result occurred by chance.