argument

In the rational method, a set of premise statements that are logically combined to yield a conclusion.

deduction/deductive reasoning

The use of a general statement as the basis for reaching a conclusion about specific examples.

Empirical method

A method of acquiring knowledge in which observation and direct sensory experience are used to obtain knowledge.

hypothesis

A statement that provides a tentative description or explanation for the relationship between variables.

induction/inductive reasoning

The use of a relatively small set of specific observations as the basis for forming a general statement about a larger set of possible observations.

method of authority

A method of acquiring knowledge in which a person relies on information or answers from an expert in the subject area.

method of faith

A variant of the method of authority in which people have unquestioning trust in the authority figure and, therefore, accept information from the authority without doubt or challenge.

method of intuition

A method of acquiring knowledge in which information is accepted on the basis of a hunch or

method of tenacity

A method of acquiring knowledge in which information is accepted as true because it has always been believed or because superstition supports it.

rational method

A method of acquiring knowledge that involves seeking answers by the use of logical reasoning.

refutable hypothesis

A hypothesis that can be demonstrated to be false. That is, the hypothesis allows the possibility that the outcome will differ from the prediction.

variability

A measure of the size of the spread of scores in a distribution.

T/F: You know that a theater ticket costs $30 and you know that you only have $25. Based on this information you decide that you cannot go to the theater. This is an example of using the empirical method.

False

T/F: Using several specific observations as the basis for constructing a general theory is an example of using deduction (or deductive reasoning).

False

T/F: Using a hypothesis to predict how people will behave is an example of induction (or inductive reasoning).

False

T/F: One critical component of the scientific method is that all answers or explanations must be demonstrated empirically.

True

T/F: Humans who participate in a research study are called research subjects.

False

A student who believes that his performance on tests is influenced by wearing a lucky hat is using the

method of tenacity

Seeking answers by using the reference materials in a college library is an example of using the

method of authority

You find some mushrooms growing in your backyard and want to find out whether or not they are poisonous, so you eat a few and see what happens. This is an example of

the empirical method of knowing or acquiring knowledge

When your doctor uses a stethoscope to listen to your heart, the doctor is gathering information by using the

empirical method

An explanation is empirical if it is based on evidence of the

senses

In a chemistry class, a group of students tried mixing two chemicals together to see what would happen. These students are using the

empirical method to gather information

One step in the scientific method involves using a hypothesis to generate a testable prediction. This process is an example of

deduction

If the individuals in a sample have characteristics that are noticeably different from the individuals in the population, then the sample is said to be:

biased

The names of all the students in a class are listed on separate pieces of paper. The teacher places the papers in a hat and mixes them thoroughly before reaching in to draw out five names. The teacher is using:

simple random sampling

A researcher would like to describe and compare the attitudes of four different ethnic groups of students at a local state college. To obtain participants for the study, the researcher should probably use ________

stratified random sampling

If your primary concern is that the composition of your sample should accurately reflect the composition of the population, then you should use:

proportionate stratified sampling

The most commonly used sampling method in psychological research is probably:

convenience sampling

A researcher who obtains a sample of preschool children by selecting individuals from a local daycare center is using:

non-probability sampling

The technique of quota sampling is most similar to:

stratified random sampling

T/F: One concern when selecting a sample is that the accessible population may not be representative of the target population.

True

T/F: When a researcher does not know the exact number of individuals in the population, it is necessary to use a nonprobability sampling method.

True

T/F: The composition of a proportionate stratified random sample usually will not accurately represent the composition of the population.

False

T/F: The most commonly used sampling methods in psychology are nonprobability sampling methods.

True

T/F: Quota sampling allows a researcher to control the composition of a convenience sample.

True

Accessible population

The easily available segment of a target population. Researchers typically select their samples from this type of population.

Biased sample

A sample with different characteristics from those of the population.

Cluster sampling

A probability sampling technique involving random selection of groups instead of individuals from a population.

Convenience sampling, also called accidental sampling and haphazard sampling.

nonprobability sampling method involving selection of individuals on the basis of their availability and willingness to respond.

Law of large numbers

the larger the sample size, the more likely it is that values obtained from the sample will be similar to the actual values for the population.

Nonprobability sampling

A method of sampling in which the population is not completely known, individual probabilities cannot be known, and the selection is based on factors such as common sense or ease with an effort to maintain representativeness and avoid bias.

Population

The entire set of individuals of interest to a researcher. Although the entire population usually does not participate in a research study, the results from the study will be generalized to the entire population. Also known as target population.

Probability sampling

A sampling method in which the entire population is known, each individual in the population has a specifiable probability of selection, and sampling is done using a random process based on the probabilities.

Proportionate stratified random sampling

A probability sampling technique that involves identifying specific subgroups to be included, determining what proportion of the population corresponds to each group, and randomly selecting individual samples from each subgroup such that the proportion in the sample exactly matches the proportion in the population. Also known as proportionate random sampling.

Quota sampling

A nonprobability sampling method; a type of convenience sampling involving identifying specific subgroups to be included in the sample and then establishing quotas for individuals to be sampled from each group.

Random process

A procedure that produces one outcome from a set of possible outcomes. The outcome must be unpredictable each time, and the process must guarantee that each of the possible outcomes is equally likely to occur.

Representative sample

A sample with the same characteristics as the population.

Representativeness

The extent to which the characteristics of the sample accurately reflect the characteristics of the population.

Sample

A set of individuals selected from a population, usually intended to represent the population in a research study.

Sampling

The process of selecting individuals to participate in a research study.

Sampling methods

The variety of ways of selecting individuals to participate in a research study. Also known as sampling techniques or sampling procedures.

Selection bias

When participants or subjects are selected in a manner that increases the probability of obtaining a biased sample. A threat to external validity that occurs when the selection process produces a sample with characteristics that are different from those in the population. Also known as sampling bias.

Simple random sampling

A probability sampling technique in which each individual in the population has an equal and independent chance of selection.

Stratified random sampling

A probability sampling technique involving identifying specific subgroups to be included in the sample, then selecting equal random samples from each pre-identified subgroup.

Systematic sampling

a sample is obtained by selecting every nth participant from a list containing the total population after a random start.

Target population

A group defined by a researcher”s specific interests; see population.

Apprehensive subject role

In a study, a participant”s tendency to respond in a socially desirable fashion rather than truthfully.

Artifact

an external factor that could influence or distort measures. Artifacts threaten both internal and external validity.

Assignment bias

A threat to internal validity that occurs when the process used to assign different participants to different treatments produces groups of individuals with noticeably different characteristics.

Carryover effects

Changes in the scores observed in one treatment condition that are caused by the lingering aftereffects of a specific earlier treatment condition.

Confounding variable

An extraneous variable (usually unmonitored) that is allowed to change systematically along with the two variables being studied. In the context of an experiment, an extraneous variable that changes systematically along with the independent variable and has the potential to influence the dependent variable. A confounding variable is a threat to internal validity.

Correlational research strategy

A general approach to research that involves measuring two or more variables in order to describe the relationship between the variables. The variables are measured and recorded to obtain a set of scores, usually two scores, for each individual; the measurements are then reviewed to identify any patterns of relationship that exist between the variables and to measure the strength of the relationship.

Curvilinear relationship

In a scatter plot o the data for a correlation, a pattern in which the data points tend to cluster in a curved line.

Demand characteristics. Demand characteristics are artifacts and can threaten both internal and external validity.

cues or features of a study that suggest to the participants what the purpose and hypothesis are, and influence the participants to respond or behave in a certain way.

Descriptive research strategy

A general approach to research that involves measuring a variable or set of variables as they exist naturally to produce a description of individual variables as they exist within a specific group.

Double-blind research

A research study in which both the researcher and the participants are unaware of the predicted outcome.

Equivalent time-samples design

A quasi-experimental design that consists of a long series of observations during which a treatment is alternately administered and then withdrawn.

Experimental research strategy

A research strategy that attempts to establish the existence of a cause-and-effect relationship between two variables by manipulating one variable while measuring the second variable and controlling all other variables.

Experimenter bias

Influence of the experimenter”s expectations or personal beliefs on the findings of a study. Experimenter bias is a type of artifact and threatens both internal and external validity.

External validity

The extent to which we can generalize the results of a research study to people, settings, times, measures, and characteristics other than those used in that study.

Extraneous variable

Any variable that exists within a study other than the variables being studied. In an experiment, any variable other than the independent and dependent variables.

Faithful subject role

In a study, a participant”s attempt to follow experimental instructions to the letter and to avoid acting on the basis of any suspicions about the purpose of the experiment.

Fatigue

A threat to internal validity that occurs when prior participation in a treatment condition or measurement procedure tires the participants and influences their performance on subsequent measurements. An example of a testing effect or an order effect.

Field

Any research setting that the participant or subject perceives as a natural environment.

Good subject role

In a study, a participant”s tendency to respond in a way that corroborates the investigator”s hypothesis.

History

A threat to internal validity from any outside event(s) that influences on the participants” scores in one treatment differently than in another treatment.

Instrumentation, Also known as instrumental bias or instrumental decay.

A threat to internal validity from changes in the measurement instrument that occur during the time a research study is being conducted.

Internal validity

The extent to which a research study produces a single, unambiguous explanation for the relationship between two variables.

Interviewer bias

The influence of the researcher verbally asking participants questions on the participants” natural responses.

Laboratory

A research setting that is obviously devoted to the discipline of science. It can be any room or space that the subject or participant perceives as artificial.

Linear relationship

In a scatter plot of the data for a correlational study, a pattern in which the data points tend to cluster around a straight line.

Maturation

A threat to internal validity from any physiological or psychological changes that occur in a participant during the time that research study is being conducted and that can influence the participant”s scores.

Multiple-treatment interference

A threat to external validity that occurs when participants are exposed to more than one treatment and their responses are affected by an earlier treatment.

Negativistic subject role

In a study, a participant”s tendency to respond in a way that will refute the investigator”s hypothesis.

Nonexperimental research strategy

A research strategy that attempts to demonstrate a relationship between two variables by comparing different groups of scores, but makes little or no attempt to minimize threats to internal validity.

Novelty effect

A threat to external validity that occurs when individuals participating in a research study (a novel situation) perceive and respond differently than they would in the normal, real world.

Order effects

Whenever individuals participate in a series of treatment conditions and experience a series of measurements, their behavior or performance at any point in the series may be influenced by experience that occurred earlier in the sequence. Order effects include carryover effects and progressive error.

Practice

A threat to internal validity that occurs when prior participation in a treatment condition or measurement procedure provides participants with additional skills that influence their performance on subsequent measurements. An example of a testing effect or an order effect.

Qualitative research

Type of research that is based on observations that are summarized and interpreted in a narrative report.

Quantitative research

Type of research that is based on measuring variables for individual participants or subjects to obtain scores, usually numerical values, that are submitted to statistical analyses for summary and interpretation.

Quasi-experimental research strategy

A research strategy that attempts to limit threats to internal validity and produce cause-and-effect conclusions (like an experiment), but lacks one of the critical components

Reactivity

Participants modification of their natural behavior in response to the fact that they are participating in a research study or the knowledge that they are being measured.

Research design

A general plan for implementing a research strategy. A research design specifies whether the study will involve groups or individual subjects, will make comparisons within a group or between groups, or specifies how many variables will be included in the study.

Research procedure

The exact, step-by-step description of a specific research study.

Research strategy

A general approach to research determined by the kind of question that the research study hopes to answer.

Sensitization, Also known as assessment sensitization or pretest sensitization.

A threat to external validity that occurs when the assessment procedure alters participants so that they react differently to treatment than they would in the real world when the treatment is used without assessment.

Single-blind research

A research study in which the researcher does not know the predicted outcome.

Statistical regression

A statistical phenomenon in which extreme scores (high or low) on a first measurement tend to be less extreme on a second measurement; considered a threat to internal validity because changes in participants” scores could be caused by regression rather than by the treatments. Also known as regression toward the mean.

Subject roles

The different ways that participants respond to experimental cues based on whatever they judge to be appropriate in the situation. Also known as subject role behavior.

Testing effects

A threat to internal validity that occurs when participants are exposed to more than one treatment and their responses are affected by an earlier treatment. Examples of testing effects include fatigue and practice. Also known as order effects.

Threat to external validity

Any characteristic of a study that limits the generality of the results.

Threat to internal validity

Any factor that allows for an alternative explanation for the results of a study.

Threat to validity

Any component of a research study that introduces questions or raises doubts about the quality of the research process or the accuracy of the research results.

Volunteer bias

A threat to external validity that occurs because volunteers are not perfectly representative of the general population.

A study addressing how many cigarettes a week are smoked by adolescents at a high school is an example of what research approach?

descriptive

The ________ strategy is an approach to research whereby two variables are measured for each individual and the relationship between the variables is examined.

correlational

Experiments allow researchers to:

answer cause-and-effect questions about the relationship between two variables

Any factor that raises doubts about the research results or the interpretation of the results is a:

threat to validity

Any factor that limits the ability to generalize the results of the study is a threat to:

external validity

In which research situation would the study be confounded?

An extraneous variable varies systematically along with the two variables being studied.

A study examining the relationship between humor and memory compares memory performance scores for one group presented with humorous sentences and a second group presented with nonhumorous sentences. The participants in both groups consist of a mixture of males and females. In this study, gender (male/female) is a(n) ________ variable.

extraneous

________ effects occur when environmental events other than the treatment influence the participants’ scores in one treatment differently than in another treatment.

History

The tendency for individuals who have extreme scores (high or low) on one measurement and to have less extreme scores on a second measurement is called:

regression toward the mean

Experimental research studies tend to have very ________ internal validity but often have relatively ________ external validity.

high, low

T/F: Qualitative research produces a written report describing and interpreting the results instead of a statistical analysis of the results.

True

T/F: The purpose of the descriptive research strategy is to describe the relationship between two variables.

False

T/F: The extent to which we can generalize the results of a study to other times, situations, environments, is external validity.

True

T/F: An extraneous variable is any variable that is part of a research study but not directly investigated.

True

T/F: A history effect is an outside, environmental variable that influences the participants’ scores in one treatment condition differently than in other conditions.

True

Control group

In a research study, the group that receives no treatment or a placebo treatment.

Dependent variable

In an experiment, the variable that is observed for changes in order to assess the effects of manipulating the independent variable. In nonexperiments and quasi-experiments the dependent variable is the variable that is measured to obtain the scores within each group. The dependent variable is typically a behavior or a response measured in each treatment condition.

Directionality problem

A correlational study can establish that two variables are related; that is, that changes in one variable tend to be accompanied by changes in the other variable. However, a correlational study does not determine which variable is the

Experiment

A study that attempts to show that changes in one variable are directly responsible for changes in a second variable. Also known as a true experiment.

Experimental group

The treatment condition in an experiment.

Experimental realism

In simulation research, the extent to which the psychological aspects of the research environment duplicate the real-world environment that is being simulated.

Field study

An experiment conducted in a setting that the participant or subject perceives as a natural environment.

Independent variable

In an experiment, the variable manipulated by the researcher. In behavioral research, the independent variable usually consists of two or more treatment conditions to which participants are exposed.

Levels

In an experiment, the different values of the independent variable selected to create and define the treatment conditions. In other research studies, the different values of a factor.

Manipulation

In an experiment, identifying the specific values of the independent variable to be examined and then creating treatment conditions corresponding to each of these values.

Manipulation check

In an experiment, an additional measure used to assess how the participants perceived and interpreted the manipulation and/or to assess the direct effect of the manipulation.

Matching

The assignment of individuals to groups so that a specific variable is balanced or matched across the groups.

Mundane realism

In simulation research, the extent to which the superficial, usually physical, characteristics of the research environment duplicate the real-world environment that is being simulated.

No-treatment control group, in an experiment…

group or condition in which the participants do not receive the treatment

Placebo

An ineffective, inert substitute for a treatment or medication.

Placebo control group

the participants receive a placebo instead of the actual treatment.

Random assignment

A procedure in which a random process is used to assign participants to treatment conditions.

Randomization

The use of a random process to help avoid a systematic relationship between two variables. The intent is to disrupt any systematic relationship that might exist between extraneous variables and the independent variable.

Simulation

In an experiment, the creation of conditions that simulate or closely duplicate the natural environment in which the behaviors being examined would normally occur.

Third-variable problem

The possibility that two variables appear to be related when, in fact, they are both influenced by a third variable that causes them to vary together.

Treatment condition

In an experiment, a situation or environment characterized by one specific value of the manipulated variable. An experiment contains two or more treatment conditions that differ according to values of the manipulated variable.

The primary purpose of manipulation in an experiment is to

establish the direction of the relationship

Dr. Jones is interested in studying how indoor lighting can influence people’s moods during the winter. A sample of 100 households is selected. Fifty of the homes are randomly assigned to the bright-light condition where Dr. Jones replaces all the lights with 100-watt bulbs. In the other 50 houses, all the lights are changed to 60-watt bulbs. After two months, Dr. Jones measures the level of depression for the people living in the houses. In this example, the level of depression is the ________ variable.

dependent

Dr. Jones is interested in studying how indoor lighting can influence people’s moods during the winter. A sample of 100 households is selected. Fifty of the homes are randomly assigned to the bright-light condition where Dr. Jones replaces all the lights with 100-watt bulbs. In the other 50 houses, all the lights are changed to 60-watt bulbs. After two months, Dr. Jones measures the level of depression for the people living in the houses. Assuming that the study uses people from different age groups, participant age would be a(n) ________ variable in the experiment.

extraneous

Any variable in a study other than those being directly studied is a(n) ________ variable.

extraneous

A researcher designs a study to determine whether female preschoolers prefer sweetened or unsweetened cereal. The researcher uses a box of sweetened colorful cereal and a box of unsweetened tan colored cereal. The research finds that the group of preschoolers ate more of the sweetened colorful cereal and therefore prefers the sweetened cereal. Which two variables are confounded in this experiment?

color of the cereal and sweetness of the cereal

In an experiment, a researcher must control extraneous variables to prevent them from becoming ________ variables.

confounding

In an experiment, participants are usually assigned to treatments using random assignment. The reason for using random assignment is:

to help control extraneous variables

A researcher has observed that children who eat more sugar tend to show a higher level of activity than children who eat less sugar. However, the researcher suspects that the apparent relationship may be explained by the fact that some children have a higher rate of metabolism which causes them to eat more and to be more active compared to children with a lower rate of metabolism who eat less and are less active. This is an example of ________.

the third-variable problem

A researcher systematically varies people’s stress levels to examine the effects of stress on performance. The researcher includes a measure of stress as:

a manipulation check

A researcher moves an experiment out of the laboratory and into the real world. This type of research is called:

a field study

T/F: In an experiment, the process of manipulation involves changing the value of the dependent variable from one treatment condition to another.

false

T/F: An experiment must have at least two different levels for the independent variable.

true

T/F: A researcher intends to compare two different treatment conditions. Participants for the first treatment are selected and tested early in the school semester, and participants for the second treatment are selected and tested late in the semester. In this study, the time-of-testing represents a confounding variable.

true

T/F: Randomization guarantees against confounding.

false

T/F: Simulation and field studies are used to increase the external validity of experiments.

true

Between-subjects design

A research design in which each of the different groups of scores is obtained from a separate group of participants. Also known as an independent-measures design.

Between-subjects experimental design

An experimental design using separate, independent groups of individuals for each treatment condition being compared. Also known as an independent-measures experimental design.

Compensatory equalization

A threat to internal validity that occurs when an untreated group demands to receive a treatment that is the same as or equivalent to the treatment received by another group in the research study.

Compensatory rivalry

A threat to internal validity that occurs when an untreated group learns about special treatment received by another group, then works extra hard to show they can perform just as well as that group. Occasionally called the John Henry effect.

Differential attrition

A threat to internal validity that occurs when attrition in one group is systematically different from the attrition in another group.

Diffusion

A threat to internal validity that occurs when a treatment effect spreads from the treatment group to the control group, usually from participants talking to each other.

Individual differences

Characteristics that differ from one participant to another.

Matched-subjects design

A research design comparing separate groups of individuals where each individual in one group is matched with a participant in each of the other groups. The matching is done so that the matched individuals are equivalent with respect to a variable that the researcher considers to be relevant to the study.

Resentful demoralization

A threat to internal validity that occurs when an untreated group learns of special treatment given to another group, and becomes less productive and less motivated because they resent the other group”s expected superiority.

Restricted random assignment

A random process for assigning individuals to groups that has a limitation to ensure predetermined characteristics (such as equal size) for the separate groups.

Single-factor multiple-group design

A research design comparing more than two groups of participants (or groups of scores) representing more than two levels of the same factor.

Single-factor two-group design

A research design comparing two groups of participants or two groups of scores representing two levels of a factor. Also known as the two-group design.

Variance within treatments

A measure of the differences between scores for a group of individuals who have all received the same treatment. The intent is to measure naturally occurring differences that have not been caused by a treatment effect. Also known as variance within groups.

Within-subjects design. Also known as repeated-measures design.

A research design in which the different groups of scores are all obtained from the same group of participants.

A design that compares different groups of scores obtained from separate groups of participants is a ________ design.

between-subjects

What best characterizes a between-subjects experimental design

Each participant is assigned to one condition of the experiment

In a between-subjects design, individual differences (participant variables) are a problem because:

they can become confounding variables and they can increase variability of the scores

In a between-subjects design the separate groups must be:

as similar in participant characteristics as possible

In a between-subjects experiment, participants are assigned to treatments using random assignment. Why is random assignment used?

It is an attempt to control participant variables so they don’t become confounding variables

The matching process involves:

measurement of the matching variable, assignment of participants to groups by means of restricted random assignment, and identification of the variable to be matched

Which procedure is not intended to minimize assignment bias as a threat to the internal validity of a between-subjects design?

random selection

Compensatory equalization occurs when:

an untreated group learns of the treatment received by another group and then demands the same treatment

The primary limitation of a two-group design is that:

it may not provide a complete picture of the relationship between the variables

When the data do not consist of numerical scores and it is impossible to examine mean differences between groups, which statistical analysis is most appropriate for a between-subjects design?

chi-square test for independence

T/F: A between-subjects experiment with 25 scores in treatment 1 and 25 scores in treatment 2 must have a total of 25 participants in the experiment.

false

T/F: Between-subjects designs are often called repeated-measures designs.

false

T/F: In a between-subjects experimental design individual differences can become a confounding variable.

true

T/F: A disadvantage of holding a variable constant is that it limits an experiment’s external validity.

true

T/F: Differential attrition can threaten the internal validity of a between-subjects experiment.

true

Anchors

On a rating scale question, the opposite extremes, identified with verbal labels, that establish the endpoints of the scale.

Archival research

Looking at historical records to measure behaviors or events that occurred in the past.

Behavior categories

Categories of behavior to be observed (such as group play, play alone, aggression, social interaction). A set of behavior categories and a list of exactly which behaviors count as examples of each are developed before observation begins.

Behavioral observation

Direct observation and systematic recording of behaviors.

Case history

A case study that does not include a treatment or intervention.

Case study design

An in-depth study and detailed description of a single individual (or a very small group). A case study may involve an intervention or treatment administered by the researcher.

Content analysis

Using the techniques of behavioral observation to measure the occurrence of specific events in literature, movies, television programs, or similar media that present replicas of behaviors.

Contrived observation, also known as structured observation.

Observation in settings arranged specifically to facilitate the occurrence of specific behaviors.

Duration method

In behavioral observation, a technique for converting observations into numerical scores that involves recording how much time an individual spends engaged in a specific behavior during a fixed-time observation period.

Event sampling

A technique of behavioral observation that involves observing and recording one specific event or behavior during the first interval, then shifting to a different event or behavior during the second interval, and so on for the full series of intervals.

Frequency method

In behavioral observation, a technique for converting observations into numerical scores that involves counting the instances of each specific behavior that occur during a fixed-time observation period.

Habituation

In behavioral observation, repeated exposure of participants to the observer”s presence until it is no longer a novel stimulus.

Idiographic approach

The study of individuals, in contrast to the study of groups.

Individual sampling

A technique of behavioral observation involving identifying one participant to be observed during the first interval, then shifting attention to a different individual for the second interval, and so on.

Interval method

In behavioral observation, a technique for converting observations into numerical scores that involves dividing the observation period into a series of intervals and then recording whether or not a specific behavior occurs during each interval.

Likert scale

A rating scale presented as a horizontal line divided into categories so that participants can circle a number or mark an X at the location corresponding to their response.

Naturalistic observation

A type of observation in which a researcher observes behavior in a natural setting as unobtrusively as possible. Also known as nonparticipant observation.

Nomothetic approach

The study of groups in contrast to the study of individuals.

Nonresponse bias

In survey research involving mailed surveys, individuals who return the survey are not usually representative of the entire group who received the survey. Nonresponse bias is a threat to external validity.

Observational research design

Descriptive research in which the researcher observes and systematically records the behavior of individuals in order to describe the behavior.

Participant observation

A type of observation in which the researcher engages in the same activities as the people being observed in order to observe and record their behavior.

Response set

On a rating-scale question, a participant”s tendency to answer all (or most) of the questions the same way.

Semantic differential

A type of rating scale question that presents pairs of bipolar of adjectives (such as happy

Survey research design

A research study that uses a survey to obtain a description of a particular group of individuals.

Time sampling

A technique of behavioral observation that involves observing for one interval, then pausing during the next interval to record all the observations. The sequence of observe-record-observe-record is continued through the series of intervals.

The goal of the descriptive research strategy is:

to describe a variable (or variables) as they exist naturally

A researcher watches children on a playground to obtain measurements of their level of aggression. This researcher is using:

naturalistic observation

A researcher who wanted to observe behaviors in a private social club would probably need to use:

participant observation

A researcher who brings dating couples into the laboratory to be observed while they are solving a problem is using:

contrived observation

What type of question produces a numerical score for each participant?

rating scale

One problem with mail surveys is nonresponse bias. This means:

individuals who return surveys may not be representative of the general population

A case study typically involves the detailed study of:

a single individual

The multiple-personality study reported in Thigpen and Cleckley’s Three Faces of Eve is an example of:

case study research

T/F: A researcher determines the amount of sugar in each child’s diet by interviewing the children’s parents. Then the researcher watches the children on a playground to obtain measurements of their level of activity. The researcher hopes to demonstrate a relationship between sugar consumption and activity level. This researcher is using the descriptive research strategy.

false

T/F: Habituation and concealment are used in behavioral observation to minimize the risk that the participants’ behavior is influenced by reacting to the presence of an observer.

true

T/F: One problem with observational research is that it can be very time consuming. However, this problem is minimized by using participant observation.

false

T/F: A political scientist uses a survey to determine whether college students’ sleeping habits are related to their grade point averages. This researcher is using the descriptive survey research design.

false

T/F: One concern with telephone surveys is interviewer bias.

true

Accuracy

The degree to which a measure conforms to the established standard.

Behavioral measure

A measurement obtained by the direct observation of an individual”s behavior.

Ceiling effect

The clustering of scores at the high end of a measurement scale, allowing little or no possibility of increases in value; a type of range effect.

Concurrent validity

The type of validity demonstrated when scores obtained from a new measure are directly related to scores obtained from a more established measure of the same variable.

Construct validity

The type of validity demonstrated when scores obtained from a measure procedure behave exactly the same as the variable itself. Construct validity is based on many research studies and grows gradually as each new study contributes more evidence.

Constructs

Hypothetical attributes or mechanisms that help explain and predict behavior in a theory. Also known as hypothetical constructs.

Convergent validity

The type of validity demonstrated by a strong relationship between the scores obtained from two different methods of measuring the same construct.

Desynchrony

Lack of agreement between two measures.

Divergent validity

A type of validity demonstrated by using two different methods to measure two different constructs. Then convergent validity must be shown for each of the two constructs. Finally, there should be little or no relationship between the scores obtained for the two different constructs when they are measured by the same method.

Face validity

An unscientific form of validity that concerns whether or not a measure superficially appears to measure what it claims to measure.

Floor effect

The clustering of scores at the low end of a measurement scale, allowing little or no possibility of decreases in value; a type of range effect.

Inter-rater reliability

The degree of agreement between two observers who simultaneously record measurements of a behavior.

Interval scale

A scale of measurement in which the categories are organized sequentially and all categories are the same size. The zero point of an interval scale is arbitrary.

Negative relationship

In a correlational study, when there is a tendency for two variables to change in opposite directions.

Nominal scale

A scale of measurement in which the categories represent qualitative differences in the variable being measured. The categories have different names but are not related to each other in any systematic way.

Operational definition

A procedure for measuring and defining a construct. An operational definition specifies a measurement procedure (a set of operations) for measuring an external, observable behavior and uses the resulting measurements as a definition and a measurement of the hypothetical construct.

Ordinal scale

A scale of measurement on which the categories have different names and are organized sequentially (for example, first, second, third).

Parallel-forms reliability

The type of reliability established by comparing scores obtained from alternate versions of a measuring instrument of the same individuals and calculating a correlation between the two sets of scores.

Physiological measure

Measurement obtained by recording a physiological activity such as heart rate.

Positive relationship

In a correlational study, when there is a tendency for the two variables to change in the same direction.

Predictive validity

The type of validity demonstrated when scores obtained from a measure accurately predict behavior according to a theory.

Range effect

The clustering of scores at one end of a measurement scale. Ceiling effects and floor effects are types of range effects.

Ratio scale

A scale of measurement in which the categories are sequentially organized, all categories are the same size, and the zero point is absolute or nonarbitrary.

Reliability

The degree of stability or consistency of measurements. If the same individuals are measured under the same conditions, a reliable measurement procedure will produce identical (or nearly identical) measurements.

Scale of measurement

The set of categories used for classification of individuals. The four types of measurement scales are nominal, ordinal, interval, and ratio.

Self-report measure

A measurement obtained by asking a participant to describe her own attitude, opinion, or behavior.

Split-half reliability

A measure of reliability obtained by splitting the items on a questionnaire or test in half, computing a separate score for each half, and then measuring the degree of consistency between the two scores for a group of participants.

Test-retest reliability

The type of reliability established by comparing the scores obtained from two successive measurements of the same individuals and calculating a correlation between the two sets of scores.

Theories

In the behavioral sciences, statements about the mechanisms underlying a particular behavior.

Validity (of a measurement procedure)

The degree to which the measurement process measures the variable it claims to measure.

Validity (of a research study)

The degree to which the study accurately answers the question it was intended to answer.

T/F: A valid measure is one that yields highly similar results across different experimental conditions.

false

T/F: A study reports that scores from the SAT are strongly related to college grade point averages. This is an example of predictive validity.

true

T/F: To establish split-half reliability you must administer the same measurement to the same group of people at two different times.

false

T/F: Classifying people as male or female is an example of measurement on a nominal scale.

true

Complete counterbalancing

In within-subjects design, using a separate group of participants for every possible order of the treatment conditions. With n different treatment conditions, there are n! (n factorial) different orders.

Counterbalancing

In a within-subjects design, a procedure to minimize threats from order effects and time-related factors by changing the order in which treatment conditions are administered from one participant to another so that the treatment conditions are matched with respect to time. The goal is to use every possible order of treatments with an equal number of individuals participating in each sequence.

Latin square

An N x N matrix where each of N different items appears exactly once in each column and exactly once in each row. Used to identify sequences of treatment conditions for partial counterbalancing.

Partial counterbalancing

A system of counterbalancing that ensures that each treatment condition occurs first for one group of participants, second for one group, third for one group, and so on, but does not require that every possible order of treatment conditions be used.

Participant attrition

The loss of participants that occurs during the course of a research study conducted over time. Attrition can be a threat to internal validity. Also known as participant mortality.

Progressive error

In a research study, changes in the scores observed in one treatment condition that are related to general experience in a research study over time, but not to a specific treatment or treatments. Common kinds of progressive error are practice effects and fatigue.

Regression

A statistical technique used for predicting one variable from another. The statistical process of finding the linear equation that produces the most accurate predicted values for Y using one predictor variable, X.

Within-subjects experimental design

An experimental design in which the same group of individuals participates in all of the different treatment conditions. Also known as a repeated-measures experimental design.

n a within-subjects research study, each participant is measured:

once in each treatment

In a within-subjects design, the term “order effects” is an alternative for the term ________.

regression

For a within-subjects experiment, one of the primary threats to internal validity is:

the risk that one treatment condition may influence scores in other treatment conditions

If one of the treatment conditions in an experiment is expected to have a permanent effect on the participants that will influence their scores in later treatments, then the researcher should probably:

use a between-subjects design

The effect of counterbalancing is:

to spread the order effects equally across the different treatment conditions

For a within-subjects study comparing two treatments, a researcher expects that practice in the first treatment will improve the participants’ scores in the second treatment. If the order of treatments is not counterbalanced so that all participants receive treatment A followed by treatment B, then the practice will influence:

scores in treatment B but not in treatment A

Latin square is used to determine the order of treatments that will be used in a within-subjects experiment comparing 5 treatments labeled A, B, C, D, and E. How many groups of participants will receive treatment E as the first treatment?

1

For an experiment that compares two treatment conditions with ten scores in each treatment, which design would require fewer subjects?

within subjects

T/F: One general concern in research is that participant variables (such as age, sex, or IQ) may become confounding variables. However, this is not a problem for within-subjects designs.

true

T/F: Counterbalancing is not used with a between-subjects design.

true

T/F: Counterbalancing involves having different groups of participants move through the series of treatments in different orders.

true

T/F: The goal of counterbalancing is to limit the possibility that order effects become a confounding variable.

true

T/F: One advantage of a two-treatment design compared to a multiple-treatment design, is that it is easier to counterbalance.

true

Alpha level

In a hypothesis test, the criterion for statistical significance that defines the maximum probability that the research result was obtained simply by chance. Also known as level of significance.

Bar graph

A frequency distribution graph in which a vertical bar indicates the frequency of each score from a nominal or ordinal scale of measurement.

Bimodal distribution

In a frequency distribution graph, a distribution of scores with two modes or two distinct peaks.

Central tendency

A statistical measure that identifies a single score that defines the center of a distribution. It provides a representative value for the entire group.

Chi-square test for independence

A hypothesis test that evaluates the statistical significance of the differences between proportions for two or more groups of participants.

Cohen”s d

A standard measure of effect size computed by dividing the sample mean difference by the sample standard deviation.

Cohen”s kappa

A calculation that corrects for chance agreement when inter-rater reliability is measured.

Cronbach”s alpha

A generalization of the Kuder-Richardson formula that computes a corrected measure of split-half reliability when each test item has more than two responses.

Degrees of freedom

The value n

Descriptive statistics

Statistical methods used to organize, summarize, and simplify the results obtained from research studies.

Effect size

The measured magnitude of the effect of an experimental treatment.

Error variance

A variance computed to measure the magnitude of differences that would be expected if the null hypothesis is true and there are no population mean differences. The denominator of the F-ratio computed in an analysis of variance.

Frequency distribution

An organized display of a set of scores that shows how many scores are located in each category on the scale of measurement.

Histogram

A frequency distribution graph in which a vertical bar indicates the frequency of each score from an interval or ratio scale of measurement.

Hypothesis test

An inferential statistical procedure that uses sample data to evaluate the credibility of a hypothesis about a population. A hypothesis test determines whether research results are statistically significant.

Independent-measures t test

In a between-subjects design, a hypothesis test that evaluates the statistical significance of the mean difference between two separate groups of participants.

Inferential statistics

Statistical methods used to determine when it is appropriate to generalize the results from a sample to an entire population.

Kuder-Richardson formula 20

A formula for computing split-half reliability that corrects for the fact that individual scores are based on only half of the total test items.

Line graph

A display in which points connected by straight lines show several different means obtained from different groups or treatment conditions.

Mean

A measure of central tendency obtained by summing the individual scores and dividing the sum by the number of scores.

Median

A measure of central tendency that identifies the score that divides the distribution exactly in half. Exactly 50% of the individuals have scores above the median and 50% have scores below the median.

Mode

A measure of central tendency that identifies the most frequently occurring score in the distribution.

Multimodal distribution

In a frequency distribution graph, a distribution of scores with more than two modes or distinct peaks.

Multiple regression equation

The resulting equation from a multiple regression analysis.

Nonparametric test

A hypothesis test that does not require numerical scores and does not involve a hypothesis about specific population parameters. Chi-square test for independence is an example of a nonparametric test.

Null hypothesis

In a hypothesis test, a statement about the population(s) or treatments being studied that says there is no change, no effect, no difference, or no relationship.

One-way ANOVA

See single-factor analysis of variance.

Parameter

A summary value that describes a population.

Parametric test

A hypothesis test that uses sample means or sample correlations to evaluate a hypothesis about the corresponding population. Parametric tests rely on sample data consisting of numerical scores.

Polygon

A frequency distribution graph in which a series of points connected by straight lines indicates the frequency of each score from an interval or ratio scale of measurement.

Repeated-measures design

See within-subjects design.

Repeated-measures t test

In a within-subjects or matched-subjects design, a hypothesis test that evaluates the statistical significance of the mean difference between two sets of scores obtained from the same group of participants.

Sampling error

The naturally occurring difference between a sample statistic and the corresponding population parameter.

Significant result

See statistically significant result.

Single-factor analysis of variance

A hypothesis test that evaluates the statistical significance of the mean differences among two or more sets of scores obtained from a single-factor multiple group design. Also known as one-way ANOVA.

Slope constant

In linear equation, Y = bX +a, b describes the slope of the line (how much Y changes when X is increased by 1 point).

Spearman-Brown formula

A formula for computing split-half reliability that corrects for the fact that individual scores are based on only half of the total test items.

Standard deviation

A measure of variability that describes the average distance from the mean; obtained by taking the square root of the variance.

Standard error

A measure of the average or standard distance between a sample statistic and the corresponding population parameter.

Statistic

A summary value that describes a sample.

Statistically significant result

In a research study, a result that is extremely unlikely (as defined by an alpha level or level of significance) to have occurred simply by chance. Also known as a significant result.

Test statistic

A summary value computed in a hypothesis test to measure the degree to which the sample data are in accord with the null hypothesis.

Two-factor ANOVA

See two-way analysis of variance.

Two-way analysis of variance

A hypothesis test that evaluates the statistical significance of the mean differences (both main effects and interaction) obtained in a two-factor research study. Also known as two-factor ANOVA.

Type I error

The conclusion, based on a hypothesis test, that a result is statistically significant when, in fact, there is no effect (no relationship) in the population.

Type II error

The conclusion, based on a hypothesis test, that a result is not statistically significant when, in fact, a real effect or relationship does exist in the population.

Variables

Characteristics or conditions that change or have different values for different individuals.

Variance

A measure of variability obtained by computing the average squared distance from the mean.

Y-intercept

In a linear equation, Y = bX + a, a, the Y-intercept, is he point at which the line intersects the Y-axis.

Cohort effects

Differences between age groups that are due to characteristics or experiences other than age. Also called generation effect.

Cohorts

Individuals who were born at roughly the same time and grew up under similar circumstances.

Cross-sectional developmental research design

A developmental design comparing different groups of individuals, each group representing a different age.

Developmental research designs

Nonexperimental research designs used to examine the relationship between age and other variables.

Differential effects

In a research study, time related threats to internal validity that affect the groups differently. For example, differential history effects, differential instrumentation effects, differential maturation, differential testing, and differential regression.

Differential research design

A nonexperimemental research design that compares pre-existing groups rather than randomly assigning individuals to groups. Usually, the groups are defined by a participant characteristic such as gender, race, or personality.

Generation effects

See cohort effects.

Interrupted time-series design

A quasi-experimental research design consisting of a series of observations before and after an event. The event is not a treatment or an experience created or manipulated by the researcher.

Longitudinal developmental research design

A developmental research design that examines development by making a series of observations or measurements over time. Typically, a group of individuals who are all the same age is measured at different points in time.

Nonequivalent control group design

A research design in which the researcher does not randomly assign individuals to groups but rather uses pre-existing groups, with one group serving in the treatment condition and another group serving in the control condition.

Nonequivalent group design

A research study in which the different groups of participants are formed under circumstances that do not permit the researcher to control the assignment of individuals to groups and the groups of participants are, therefore, considered nonequivalent.

One-group pretest-posttest design

A nonexperimental design involving one measurement before treatment and one measurement after treatment for a single group of participants.

Posttest-only nonequivalent control group design

A nonexperimental design in which one group is observed (measured) after receiving a treatment, and a second, nonequivalent group is measured at the same time but receives no treatment.

Pre-post designs

Quasi-experimental and nonexperimental designs consisting of a series of observations made over time. The goal is to evaluate the effect of an intervening treatment or event by comparing observations made before versus after the treatment.

Pretest

A quasi-experimental research design comparing two nonequivalent groups; one group is measured twice, once before treatment is administered and once after. The other group is measured at the same two times but receives no treatment.

Quasi-independent variable

In a quasi-experimental or nonexperimental research study, the variable that differentiates the groups or conditions being compared. Similar to the independent variable in an experiment.

Single-subject designs

Experimental research designs that use the results from a single participant or subject to establish the existence of a cause-and-effect relationship. Also known as single-case designs.

Time-series design

A quasi-experimental research design consisting of a series of observations before a treatment or event and a series of observations after the treatment. The researcher administers the treatment.

Combined strategy

A factorial study that combines two different research strategies such as experimental and nonexperimental or quasi-experimental in the same factorial design.

Factor

A variable that differentiates a set of groups or conditions being compared in a research study. In an experimental design, a factor is an independent variable.

Factorial design

A research design that includes two or more factors.

Higher-order factorial design

A factorial research design with more than two factors.

Interaction between factors

In a factorial design, whenever one factor modifies the effects of a second factor. If the mean differences between the treatment conditions are explained by the main effects, then the factors are independent and there is no interaction. Also, when the effects of one factor depend on the different levels of a second factor. Indicated by the existence of nonparallel (converging or crossing) lines in a graph showing the means for a two-factor design. Also known as interaction.

Level

In a single-subject research study, the overall magnitude for a series of observations. A consistent level occurs when measurements in a series are all approximately the same magnitude.

Main effect

In a factorial study, the mean differences among the levels of one factor.

Mixed design

A factorial study that combines two different research designs such as between-subjects and within-subjects in the same factorial design.

Single-factor design

A research study with one independent variable or one quasi-independent variable.

Three-factor design

A research study involving three factors.

Two-factor design

A research study involving two factors.