PSYC 204 Final

A Pearson correlation of r = +0.9 indicates that a graph of the data would show: a. points clustered close to a line that slopes up to the right. b. points widely scattered around a line that slopes up to the right. c. points clustered close to a line that slopes down to the right. d. points widely scattered around a line that slopes down to the right.

A

A graph of a two-factor study indicates an interaction when the lines on the graph: a. cross or converge. b. are steep in slope. c. are parallel. d. None of the other three choices demonstrate an interaction.

A

A research study records a score measuring alcohol use and a score measuring income level for each individual in a group of 40-year-old men. The study intends to determine whether there is a relationship between the two variables. This study is an example of the ________ research strategy. a. correlational b. experimental c. nonexperimental d. descriptive

A

A researcher decides to use only male participants in an experiment comparing two treatment conditions. For this study, what method is being used to control participant gender? a. holding constant b. limiting the range c. randomization d. matching

A

A researcher who is examining the effects of temperature and humidity on the eating behavior of rats uses a factorial experiment comparing three different temperatures (70˚, 80˚, and 90˚) and two humidity conditions (low and high). How many factors are in the experiment? a. 2 b. 6 c. 3 d. 1

A

A treatment phase is defined as: a. a series of observations made when a treatment is being administered. b. the first observation made after a treatment is administered. c. the boundary between pre-treatment observations and post-treatment observations. d. the amount of change between the final observation before treatment and the first observation after treatment.

A

Experiments allow researchers to: a. answer cause-and-effect questions about the relationship between two variables. b. observe naturally occurring behavior. c. eliminate experimenter bias. d. answer questions about the existence of a relationship between two variables.

A

For an experiment comparing two treatments, the researcher selects participants so that each treatment condition has 20 males and 10 females. For this study, what method is being used to control participant gender? a. matching b. holding constant c. randomization d. limiting the range

A

In a between-subjects experiment, participants are assigned to treatments using random assignment. Why is random assignment used? a. It is an attempt to control participant variables so they don't become confounding variables. b. It gives the experimenter an opportunity to measure participant variables that might influence the outcome of the experiment. c. It allows the experimenter to manipulate participant variables. d. It helps to ensure that the participants in the study are representative of the general population.

A

In a graph of single-subject research data, a clear indication of a treatment effect is: a. a clear and immediate change in either the level or trend when the treatment is initiated. b. a continuation of the same average level from one phase to the next. c. a continuation of a clear trend from one phase to the next. d. a gradual change in behavior that becomes clear several observations after the treatment is initiated.

A

In a time series design, the series of observations before treatment helps reduce threats to internal validity because: a. if an outside factor is influencing the scores, the effects should be seen before the treatment is administered. b. a series of observations is more reliable than a single observation. c. a series of observations has more validity than a single observation. d. if an outside factor is influencing the scores, it can be stopped before the treatment is administered.

A

The basic threat to internal validity for a nonequivalent groups design is: a. assignment bias. b. regression. c. reactivity. d. history.

A

Which of the following is NOT a method for trying to prevent a participant characteristic (such as age or gender) from becoming a confounding variable in a between-subjects experiment? a. Randomly select the participants from the population. b. Match the groups with respect to the participant characteristic. c. Hold the participant characteristic constant. d. Randomly assign participants to treatment conditions.

A

Which of the following is a possible outcome from a 2 x 2 factorial design? a. no main effect for either factor and one interaction b. a main effect for one factor, no main effect for the other factor, and two interactions c. The other three choices are all possible outcomes. d. two main effects and two interactions

A

Which research design is used by a researcher comparing self-esteem scores for children from divorced families versus scores for children from families with no divorce? a. differential research design b. pretest-only nonequivalent control group design c. time-series design d. pretest-posttest nonequivalent control group design

A

Monotonic relationship

A consistently one-directional relationship between two variables. As one variable increases, the other variable also tends to increase or tends to decrease. The relationship can be either linear or curvilinear.

Pearson correlation

A correlation used to evaluate linear (straight-line) relationships.

Spearman correlation

A correlation used with ordinal data or to evaluate monotonic relationships.

Cross-sectional developmental research design

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

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.

Higher-order factorial design

A factorial research design with more than two factors.

Mixed design

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

Combined strategy

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

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, but does not attempt to describe or explain relationships between variables.

Correlational research strategy

A general approach to research that involves measuring two or more variables for each individual to describe the relationship between the variables. The measurements are reviewed to identify any patterns of relationship that exist between the variables and to measure the strength of the relationship; however, no attempt is made to explain the relationship.

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.

Multiple-baseline across subjects

A multiple-baseline design in which the initial baseline phases correspond to the same behavior for two separate participants.

Multiple-baseline across situations

A multiple-baseline design in which the initial baseline phases correspond to the same behavior in two separate situations.

Multiple-baseline across behaviors

A multiple-baseline design in which the initial baseline phases correspond to two separate behaviors for the same participant.

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.

One-group pretest-posttest design

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

Differential research design

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

Random assignment

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

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.

Pretest-posttest nonequivalent control group design

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.

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 or event. A treatment is a manipulation administered by the researcher and an event is an outside occurrence that is not controlled or manipulated by the researcher.

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

Negative relationship

A relationship in which the two variables or measurements tend to change together in opposite directions.

Positive relationship

A relationship in which the two variables or measurements tend to change together in the same direction.

Matched-subjects design

A research design comparing separate groups of individuals in which 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.

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.

Within-subjects design

A research design in which the different groups of scores are all obtained from the same group of participants. Also known as repeated-measures design.

Nonequivalent control group design

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

Factorial design

A research design that includes two or more factors.

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.

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 or to explain the relationship

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 or to explain the relationship.

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.

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—either manipulation or control—that is necessary for a true experiment. Typically compares groups or conditions that are defined with a non-manipulated variable.

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—either manipulation or control—that is necessary for a true experiment. Typically compares groups or conditions that are defined with a nonmanipulated variable.

Double-blind research

A research study in which both the researcher and the participants are unaware of the predicted outcome for any specific participant

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.

Single-blind research

A research study in which the researcher does not know the predicted outcome for any specific participant.

Three-factor design

A research study involving three independent or quasi-independent variables.

Two-factor design

A research study involving two independent or quasi-independent variables.

Survey research design

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

Single-factor design

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

Multiple-baseline design

A single-subject design that begins with two simultaneous baseline phases, then initiates a treatment for one baseline, and, at a later time, initiates the treatment for the second baseline.

Reversal design

A single-subject experimental design consisting of four phases: a baseline phase, a treatment phase, a return-to-baseline phase, and a second treatment phase

ABAB design

A single-subject experimental design consisting of four phases: a baseline phase, a treatment phase, a return-to-baseline phase, and a second treatment phase. Also known as a reversal design.

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

Regression toward the mean

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. See statistical regression.

Multiple regression

A statistical technique used for studying multivariate relationships. The statistical process of finding the linear equation that produces the most accurate predicted values for Y using more than one predictor variable.

Correlation

A statistical value that measures and describes the direction and degree of relationship between two variables. The sign (+/) indicates the direction of the relationship. The numerical value (0.0 to 1.0) indicates the strength or consistency of the relationship. The type (Pearson or Spearman) indicates the form of the relationship. Also known as correlation coefficient.

True experiment

A study that attempts to show that changes in one variable are directly responsible for causing changes in a second variable

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.

Volunteer bias

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

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.

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.

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.

History

A threat to internal validity from any outside event that influences the participants' scores in one treatment differently than in another treatment.

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.

Instrumentation

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

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.

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.

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.

Differential attrition

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

Testing effects

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

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.

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

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.

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.

Repeated-measures experimental design

An experimental design in which the same group of individuals participates in all of the different treatment conditions

Within-subjects experimental design

An experimental design in which the same group of individuals participates in all of the different treatment conditions

Between-subjects experimental design

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

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 provides an alternative explanation for the observed relationship and, therefore, is a threat to internal validity.

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.

Latin square

An n × n matrix in which 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.

Threat to external validity

Any characteristic of a study that limits the ability to generalize the results.

Threat to internal validity

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

Demand characteristics

Any potential cues or features of a study that (1) suggest to the participants what the purpose and hypothesis are, and (2) influence the participants to respond or behave in a certain way. Demand characteristics are artifacts and can threaten the validity of the measurement, as well as both internal and external validity.

Field

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

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.

A case study typically involves the detailed study of: a. a single group such as a fraternity or an athletic team. b. a single disease or psychiatric disorder. c. a single clinical treatment. d. a single individual.

B

A negative value for a correlation indicates: a. increases in X tend to be accompanied by increases in Y. b. increases in X tend to be accompanied by decreases in Y. c. a much weaker relationship than if the correlation were positive. d. a much stronger relationship than if the correlation were positive.

B

A researcher is conducting an experiment comparing three treatment conditions. If the researcher uses a between-subjects design, there will be ________ score(s) for each participant; but if a within-subjects design is used, there will be ________ score(s) for each participant. a. 3; 3 b. 1; 3 c. 3; 1 d. 1; 1

B

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. a measure of the dependent variable. b. a manipulation check. c. a measure of extraneous variables. d. a control for confounding variables.

B

An interaction between factors cannot occur unless: a. there is a main effect for both of the factors. b. The existence of an interaction is independent of the main effects. c. there is a main effect for at least one of the two factors. d. there is no main effect for either of the two factors.

B

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. a. independent b. dependent c. extraneous d. correlational

B

In a 3 x 4 factorial design there are ________ main effect(s) and ________interaction(s) possible. a. 1; 2 b. 2; 1 c. 3; 4 d. 2; 3

B

In a between-subjects design, you can increase the likelihood of finding a difference between the treatment conditions by: a. taking steps to maximize variance within groups. b. taking steps to minimize variance within groups. c. including several dependent variables in your experiment. d. including several independent variables in your experiment.

B

In a between-subjects design: a. one score is obtained for each treatment condition for each participant. b. only one score is obtained for each participant. c. each score represents multiple participants. d. at least two scores are obtained for each participant.

B

In a typical pre-post study: a. two groups are measured before and after a treatment. b. one group is measured before and after a treatment. c. two groups are measured after a treatment. d. one group is measured after a treatment.

B

In the notation for single-case designs: a. the letter A identifies the first treatment condition. b. the letter C identifies a second treatment phase. c. the letter B identifies the baseline phase. d. All of the other choices are correct.

B

The Spearman correlation measures: a. the degree of curvilinear relationship. b. the degree of monotonic relationship. c. the degree of linear relationship. d. the degree to which the relationship is causal.

B

The effect of counterbalancing is: a. to subtract out order effects along with the individual differences. b. to spread order effects equally across the different treatment conditions. c. to separate order effects from the treatment effects. d. to eliminate order effects.

B

The goal of the descriptive research strategy is: a. to describe an individual person or patient in great detail. b. to describe a variable (or variables) as they exist naturally. c. to establish the existence of a cause and effect relationship between variables. d. to describe the relationship between two variables.

B

When one treatment condition has a lasting effect on the participants and influences their scores in later treatments, the study is confounded by: a. history effects. b. carryover effects. c. progressive error. d. instrumentation.

B

Which of the following is the correct description for a research study comparing problem solving scores obtained under three different levels of temperature? a. two-factor design b. single-factor design c. factorial design d. three-factor design

B

Which research design is commonly used to help establish the reliability or validity of a measurement procedure? a. the survey research design b. the correlational design c. the observational research design d. the case study design

B

Which research strategy is not concerned with examining relationships between variables? a. quasi-experimental b. descriptive c. correlational d. experimental

B

A Pearson correlation of r = -0.25 indicates that a graph of the data would show: a. points widely scattered around a line that slopes up to the right. b. points clustered close to a line that slopes up to the right. c. points widely scattered around a line that slopes down to the right. d. points clustered close to a line that slopes down to the right.

C

A problem with a longitudinal design is that the results may be distorted by: a. assignment bias. b. differential history effects. c. participant attrition. d. cohort effects.

C

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? a. children's gender and amount of eating b. color of the cereal and children's gender c. color of the cereal and sweetness of the cereal d. sweetness of the cereal and amount of eating

C

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: a. the directionality problem. b. the manipulation check problem. c. the third-variable problem. d. the extraneous variable problem.

C

A researcher records participants' weights every Friday for three weeks prior to administering a diet education program and for three weeks following the program. This study is an example of: a. an interrupted time-series design. b. a longitudinal design. c. a time-series design. d. a cross-sectional design

C

An advantage of holding a variable constant rather than using random assignment to form your groups is that: a. holding a variable constant ensures a nonbiased sample. b. holding a variable constant reduces error due to participant differences. c. holding a variable constant guarantees that there is no systematic relationship between participant characteristics and the treatment conditions. d. holding a variable constant is easier than randomization.

C

As the values for one variable decrease from one person to another, the values for a second variable also tend to decrease. This is an example of a ________ relationship. a. negative b. These data show no consistent relationship. c. positive d. curvilinear

C

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. a. independent b. confounding c. extraneous d. dependent

C

For an experiment that compares two treatment conditions with ten scores in each treatment, which design would require fewer subjects? a. matched-subjects b. All would require the same number of subjects. c. within-subjects d. between-subjects

C

In a between-subjects experiment, when the participants in one group have characteristics that are noticeably different from those in another group, the ________ of the study is threatened. a. reliability b. accuracy c. internal validity d. external validity

C

In an experiment, participants are usually assigned to treatments using random assignment. The reason for using random assignment is: a. to allow the experimenter to manipulate participant variables. b. a required component of all experiments. c. to help control extraneous variables. d. to allow the experimenter to manipulate environmental variables.

C

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? a. 5 b. cannot answer without more information c. 1 d. 0

C

Which of the following is not a time-related threat to internal validity for a within-subjects experiment? a. instrumentation b. maturation c. assignment bias d. history

C

Which of the following is the correct description for a research study comparing problem solving ability for girls versus boys under three different levels of temperature? a. 2 x 2 x 3 design b. None of the other options is an accurate description. c. 2 x 3 design d. 2 x 2 design

C

Which research strategies produce similar data structures that use the same statistical analyses? a. correlational and experimental b. descriptive and correlational c. experimental, quasi-experimental, and nonexperimental d. correlational and nonexperimental

C

Which statement best characterizes a between-subjects experimental design? a. Participants with different characteristics make up the different conditions of the experiment. b. Participants are randomly selected from two different populations. c. Each participant is assigned to one condition of the experiment. d. Each participant is assigned to every condition of the experiment.

C

Carryover effects

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

Individual differences

Characteristics that differ from one participant to another

A quasi-experimental design: a. controls extraneous variables, similar to an experiment. b. manipulates one variable, similar to an experiment. c. makes no attempt to minimize threats to validity. d. makes some attempts to minimize threats to validity.

D

A researcher watches children on a playground to obtain measurements of their level of activity. Then the researcher watches the children's caregivers on the playground to obtain measurements of their level of verbal reprimanding of children. The researcher hopes to demonstrate that the caregivers' verbal reprimanding is related to the children's activity level. This researcher is using the: a. descriptive research strategy. b. experimental research strategy. c. scientific research strategy. d. correlational research strategy

D

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 non-humorous sentences. The participants in both groups consist of a mixture of males and females. In this study, gender (male/female) is a(n) ________ variable. a. dependent b. independent c. confounding d. extraneous

D

An experiment that uses a different group of participants for each treatment condition is called a ________ design. a. matched groups b. single-subjects c. within-subject d. between-subjects

D

Any factor that limits the ability to generalize the results of the study is a threat to: a. internal validity. b. reliability. c. accuracy. d. external validity.

D

Dr. Jones hopes to demonstrate that children who eat a more nutritious breakfast also tend to have more academic success than their peers. If this result is obtained, then ________ would be the predictor variable and ________ would be the criterion variable for the study. a. the children; the level of success b. the level of success; the nutrition in the breakfast c. those who eat a high nutrition breakfast; those who eat a low nutrition breakfast d. the nutrition in the breakfast; the level of success

D

For a within-subjects experiment, one of the primary threats to internal validity is: a. individual differences that may exist within treatment conditions. b. the risk that one (or more) of the treatment conditions will have no influence on the participants' scores. c. individual differences that may exist between treatment conditions. d. the risk that participation in one treatment condition may influence scores in other treatment conditions.

D

In a within-subjects research study, factors that change over time, such as history and maturation, can be threats to: a. neither internal nor external validity. b. external validity. c. both internal and external validity. d. internal validity.

D

In single-subject research, a group of observations of the same individual under the same conditions is known as: a. a data set. b. a time series. c. a sequence. d. a phase.

D

One of the primary advantages of a pretest-posttest nonequivalent control group design, in comparison to other nonequivalent group designs, is: a. the posttest scores can help reduce the threat of differential history. b. the posttest scores can help reduce threats from history effects. c. the pretest scores can help reduce the threat of differential history. d. the pretest scores can help reduce the threat of assignment bias.

D

Single-subjects research studies tend to have: a. statistical significance even though they do not have practical significance. b. neither practical nor statistical significance. c. both practical and statistical significance. d. practical significance even though they do not have statistical significance.

D

Which of the following identifies a potential problem with Internet surveys? a. It can be difficult to find a group of participants who share a specific interest. b. It can be difficult to control or even know the composition of the sample. c. They tend to be costly and inefficient. d. They limit flexibility in presenting questions and response alternatives.

D

Which of the following pairs of variables should produce a negative relationship? a. IQ and weight for a group of third-grade students b. model year (2003, 2004, etc.) and price for a used Honda c. driving distance from college and weekly cost of gas for a group of commuting college students d. number of hours studying and number of errors on a math exam

D

________ effects occur when environmental events other than the treatment influence the participants' scores in one treatment differently than in another treatment. a. Subject selection bias b. Volunteerism c. Fatigue d. History

D

Directionality problem

Demonstrating that changes in one variable tend to be accompanied by changes in another variable simply establishes that the two variables are related. The remaining problem is to determine which variable is the cause and which is the effect.

Observational research design

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

Cohort effects

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

Time-related variables

Environmental or participant variables that change over time. A threat to the internal validity of studies that compare measures of the same individuals taken at different times.

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

Predictor variable

In a correlational study, a researcher often is interested in the relationship between two variables to use knowledge about one variable to help predict or explain the second variable. In this situation, the first variable is called the predictor variable.

Criterion variable

In a correlational study, a researcher often is interested in the relationship between two variables to use knowledge about one variable to help predict or explain the second variable. In this situation, the second variable (being explained or predicted) is called the criterion variable.

Statistical significance of a correlation

In a correlational study, the correlation in the sample is large enough that it is very unlikely to have been produced by random variation, but rather represents a real relationship in the population.

Interaction

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

Main effect

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

Curvilinear relationship

In a graph showing the changing values of two variables, a pattern in which the data points tend to cluster around a curved line

Linear relationship

In a graph showing the changing values of two variables, a pattern in which the data points tend to cluster around a straight line.

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.

Control group

In a research study, a condition that involves no treatment or a placebo treatment

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

Phase

In a single-subject research design, a series of observations of the same individual under the same conditions

Trend

In a single-subject research study, a consistent difference in direction and magnitude from one measurement to the next in a series.

Baseline phase

In a single-subject research study, a series of baseline observations identified by the letter A.

Treatment phase

In a single-subject research study, a series of treatment observations identified by the letter B.

Baseline observations

In a single-subject research study, observations or measurements made while no treatment is being administered

Phase change

In a single-subjects research study, a change in the conditions from one phase to another, usually involving administering or stopping a treatment.

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.

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. The researcher then manipulates the variable by changing from one condition to another.

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.

Dependent variable

In an experiment, the variable that is observed for changes 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.

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.

Artifact

In the context of a research study, an external factor that could influence or distort measures. Artifacts threaten the validity of the measurement, as well as both internal and external validity.

Cohorts

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

Developmental research designs

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

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. Reactivity is an artifact and can threaten the validity of the measurement, as well as both internal and external validity.

Quantitative research

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.

Qualitative research

Research that is based on observations that are summarized and interpreted in a narrative report.

Matching

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

Stability

The degree to which a series of observations shows a consistent level or trend.

Validity

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

Internal validity

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

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.

Experimenter bias

The influence on the findings of a study from the experimenter's expectations about the study. Experimenter bias is a type of artifact and threatens the validity of the measurement, as well as both internal and external validity.

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.

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.

Coefficient of determination, r2

The squared value of a correlation that measures the percentage of variability in one variable, which is determined or predicted by its relationship with the other variable.

Nomothetic approach

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

Idiographic approach

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

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.

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.

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. Also known as testing effects

Extraneous variables

any variable in a research study other than the specific variables being studied

Counter Balancing

changing the order in which treatment conditions are administered

Iterative process

researcher comes up with themes, but then goes back to check their own interpretation against what the subject actually said