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Archival research: When you use existing sources of information for research. Sources include statistics, surveys and records.
Examples of non experimental studies are?: Surveys, questionnaires and interviews
Why are surveys used?: To gather information, study relationships between variables
What are the 3 types of survey questions?: Attitudes and beliefs, facts and demographics, and behaviours
Examples of probability sampling?: Simple random sampling, Stratified random sampling, cluster sampling
Examples of non-probability sampling?: Haphazard sampling and quota sampling
What are the two methods of administering surveys?: Written questionnaires and interviews
What does the 68-95-99 rule apply for?: Normal distribution
Sample size does what do the confidence interval?: It increases or decreases the confidence interval
What are the 2 ways to manipulate the independent variable?: To vary it quantitatively and vary it qualitatively.
How to reduce error variance?: Hold extraneous variables constant, random assignment.
What is the latin square formula for ABCDEF?: A, B, L, C, L-1, D, L-2, etc. = ABFCED
What is the simplest type of factorial design?: 2x2
Main effect is shown when?: There is a big difference between the subgroups of a variable
Interaction is shown when?: It is shown when you draw the line on the bar graph from the top lefts and they cross
What are the types of questions in surveys?: Dichotomous, Nominal, Ordinal, Interval, Filter
What are dichotomous answers on a survey?: Where you have two options for answers such as yes or no.
What are nominal answers on a survey?: Where the answers are categories
What are ordinal answers on a survey?: Where the answers are ranked on a scale
What are interval answers on a survey?: Where the answers are ordered based on strength
What are filter answers on a survey?: Where a question filters to see if the next question is suitable for you to answer.
Case study: A descriptive account of the behaviour, past history and other relevant factors concerning a specific individual.
Coding system: A set of rules used to categorize observations.
Concealed observation: A type of naturalistic observation in which the researcher assumes a participant role in the setting he or she is researching, but conceals the purpose of the research.
Content analysis: Systematic analysis of the content of written records.
Naturalistic observation: Descriptive method in which observations are made in a natural social setting. Also called field observation.
Participant observation: A type of naturalistic observation in which the researcher assumes a role in the setting he or she is researching. The researcherâ€™s participation may or may not be concealed.
Qualitative approach: An approach to research that emphasizes peopleâ€™s lived experiences in their own words, and the researcherâ€™s interpretation of those experiences.
Quantitative approach: An approach to research that emphasizes scientific empiricism in design, data collection, and statistical analyses.
Reactivity: A problem of measurement in which the measure changes the behaviour being observed.
Systematic observation: Observation of one or more specific variables, usually made in a precisely defined setting.
Closed-ended questions: Questions that offer respondents limited options. A multiple choice question is an example.
Cluster sampling: A method of sampling in which clusters of individuals are identified. Clusters are sampled, and then all individuals in each cluster are included in the sample.
Confidence interval: An interval of values that will capture the true population value a certain proportion of times (i.e. 95 percent) that the confidence interval is calculated in that way.
Convenience sampling/Haphazard sampling: Selecting participants in a haphazard manner, usually on the basis of availability, and not with regard to having a representative sample of the population; a type of non-probability sampling. Also called haphazard sampling.
External validity: The degree to which the results of an experiment may be generalized.
Focus group: A qualitative method of data collection in which six to ten people are interviewed together about a particular topic
Graphic rating scale: A type of closed-ended response where two words appear on either side of a solid line. Participants place a mark on the line indicating their relative preference for one or the other word.
Interviewer bias: Intentional or unintentional influence exerted by an interviewer in such a way that the actual or interpreted behaviour of respondents is consistent with the interviewerâ€™s expectations.
Non-probability sampling: Type of sampling procedure in which one cannot specify the probability that member of the population will be included in the sample.
Open-ended questions: Questions that offer respondents no restrictions as to how to respond to the prompt (i.e. an essay question)
Panel study: In survey research, questioning the same people at two or more points in time.
Population: The defined group of individuals from which the sample is drawn.
Probability sampling: Type of sampling procedure in which one is able to specify the probability that any member of the population will be included in the sample
Quota sampling: A sampling procedure in which the sample is chosen to reflect the numerical composition of various subgroups in the population. A convenience sampling technique is used to obtain the sample
Random sample: When everyone in a given population is equally likely to have been selected to participate in the study, that sample is said to be random.
Rating scales: Closed-ended response options that enable participants to indicate the degree to which they endorse a particular statement
Response rate: The percentage of people selected for a sample who actually completed a survey
Response set: A pattern of individual response to questions on a self-report measure that is not related to the content of the questions
Sampling: The process of choosing members of a population to be included in a sample.
Sampling error: The degree to which the statistic calculated from a sample deviates from the true population value
Sampling frame: The individuals or clusters of individuals in the population who might actually be selected for inclusion in the sample.
Semantic differential scale: A type of closed-ended response where two words appear on either side of a series of dashed lines. Participants place a mark on the sash indicating their relative preference for one or the other word.
Simple random sampling: A sampling procedure in which each member of the population has an equal probability of being included in the sample
Standard error: Spread of averages around the average of the averages in a sampling distribution
Stratified random sampling: A sampling procedure in which the population is divided into strata followed by random sampling from each stratum
Survey research: Questionnaires and interviews carefully designed to ask people information about themselves.
â€œYea-sayingâ€ and â€œnay-sayingâ€ response sets: The tendency for some survey respondents to agree or disagree with the vast majority of questions being asked, regardless of the question; introduces error into the measure.
Confounding variable: An uncontrolled variable that is impossible to separate from a variable of interest.
Contrast effect: In a repeated measures design, occurs when participantsâ€™ responses on a later condition are affected by a particular experience they had in an earlier condition.
Counterbalancing: A method of controlling for order effects in a repeated measures design by either including all orders of treatment presentation or randomly determining the order for each participant.
Fatigue effect: When participants perform worse over the course of a study simply because of effort or the passage of time, problematic in repeated measures design.
Independent groups design: An experiment in which different participants are assigned to each group. Also called between subjects design.
Internal validity: The certainty with which results of an experiment can be attributed to the manipulation of the independent variable rather than to some other, confounding variable.
Latin square: A technique to control for order effects without having all possible orders
Matched pairs design: A method of assigning participants to groups in which pairs of participants are first matched on some characteristic and then individually assigned randomly to groups.
Mortality: The loss of participants who decide to leave an experiment. Mortality is a threat to internal validity when the mortality rate is related to the nature of the experimental manipulation.
Order effect: In a repeated measures design, the effect that the order of introducing treatment has on the dependent variable.
Posttest-only design: A true experimental design in which the dependent variable is measured only once, after manipulation of the independent variable.
Practice effect: When participants perform better over the course of a study simple because they are more experienced with the task; particularly problematic in repeated measures designs.
Pretest-posttest design: A true experimental design in which the dependent variable is measured both before (pretest) and after (posttest) manipulation of the independent variable.
Random assignment: Controlling for the effects of extraneous variables by ensuring that participants in an experiment are assigned to condition in a manner determined entirely by chance.
Repeated measures design: An experiment in which the same participants are assigned to each group.
Selection differences: Differences in the type of participants who make up each group in an experimental design, this situation occurs when participants elect which group they are to be assigned to.
Behavioural measure: An operational definition that involves directly observing and precisely recording a human or animalâ€™s behaviour.
Ceiling effect: Failure of a measure to detect a difference because it was too easy.
Confederate: A person posing as a participant in an experiment who is actually part of the experiment.
Debriefing: Explanation of the purposes of the research that is given to participants following their participation in the research.
Demand characteristics: Cures that inform the participant how he or she is expected to behave.
Double-blind procedure: An experiment in which neither the experimenter nor the participant knows to which condition the participant has been assigned.
Experimenter bias (experimenter expectancy effects): Any intentional or unintentional influence that the experimenter exerts on participants to confirm the hypothesis under investigation.
Filler items: Item included in a questionnaire measure to help disguise the true purpose of the measure.
Floor effect: Failure of a measure to detect a difference because it was too difficult.
Manipulation check: A measure used to determine whether the manipulation of the independent variable has had its intended effect on a participant
Manipulation strength: The degree to which levels of an independent variable differ from each other. In a weak manipulation, conditions are subtly different; conditions are maximally different in a strong manipulation.
Physiological measure: An operational definition that involves observing and recording a response of the body.
Pilot study: A small-scale study conducted prior to conducting an actual experiment; designed to test and refine procedures.
Placebo group: In drug research, a group given an inert substance to assess the psychological effect of receiving a treatment.
Self-report measure: An operational definition of a variable that involves asking people to explicitly indicate something about themselves (i.e. personality, behaviour attitudes).
Sensitivity: The ability of a measure to detect differences between groups.
Single-blind procedure: An experiment in which participants do not know to which condition they have been assigned, but the experimenter does.
Staged manipulations: An operational definition that involves creating a situation in which the independent variable is manipulated; participants then experience the situation and their responses are recorded. Deception is often used to conceal the fact that the situation is a ruse.
Straightforward manipulations: Operational definitions that involve manipulating the independent variable using instructions or other stimulus materials in a simple way.
Cell: A term sometimes used to refers to one condition in an experiment, or to a combination of conditions in a complex factorial experimental design.
Factorial design: A design in which all levels of each independent variable are combined with all levels of the other independent variables. A factorial design allows investigation of the separate main effects and interactions of two or more independent variables.
Interaction: The differing effect of one independent variable on the dependent variable, depending on the particular level of another independent variable.
IV x PV design: A factorial design that includes both an experimental independent variable (IV) and non-experimental participant variable (PV).
Levels: Term sometimes used to denote conditions in an experimental design.
Main effect: The direct effect of an independent variable on a dependent variable.
Mixed factorial design: A design that includes both independent groups (between-subjects) and repeated measures (within-subjects) variables.
Moderator variable: A variable that influences the nature of the relationship between two other variables (an independent variable and a dependent variable). In a factorial design, the effect of the moderator variable is revealed as an interaction.
Simple main effect: In a factorial design, the effect of one independent variable at a particular level of another independent variable.
Baseline: In a single case design, the participantâ€™s behaviour during a control period before introduction of the manipulation.
Cohort effects: A cohort is a group of people born at about the same time and exposed to the same societal events; cohort effects are confounded with age in a cross-sectional study.
Control series design: An extension of the interrupted time series quasi-experimental design in which there is a comparison or control group.
Cross-sectional method: A developmental research method in which persons of different ages are studied at only one point in time; conceptually similar to an independent group design.
History effects: As a threat to the interval validity of an experiment, refers to outside events that are not part of the manipulation that could be responsible for the results.
Instrument decay: As a threat to internal validity, the possibility that a change in the characteristics of the measurement instrument is responsible for the results.
Interrupted time series design: A design in which the effectiveness of a treatment is determined by examining a series of measurements made over an extended time period both before and after the treatment is introduced. The treatment is not introduced at a random point in time.
Longitudinal method: A developmental research method in which the same persons are observed repeatedly as they grow older; conceptually similar to a repeated measured design.
Maturation effects: As a threat to internal validity, the possibility that any naturally occurring change within the individual is responsible for the results.
Multiple baseline design: Observing behaviour before and after a manipulation under multiple circumstances (across different individuals, different behaviours, or different settings).
Non-equivalent control group design: A quasi-experimental design in which non-equivalent groups of participants participate in the different experimental groups, and there is no pretest.
Non-equivalent control group pretest-posttest design: A quasi-experimental design in which non-equivalent groups are used, but a pretest allows assessment of equivalency and pretest-posttest changes.
One-group posttest-only design: A quasi-experimental design that has no control group and no pretest comparison; a very poor design in terms of internal validity.
One-group pretest-posttest design: A quasi-experimental design in which the effect of an independent variable is inferred from the pretest-posttest difference in a single group.
Program evaluation: Research designed to evaluate programs (i.e. social reforms, innovations) that are designed to produce certain change or outcomes in a target population.
Quasi-experimental designs: Types of designs that approximate the control features of true experiments to infer that a given treatment did have its intended effect.
Regressions toward the mean (statistical regression): Principle that extreme scores on a variable tend to be closer to the mean when a second measurement is made.
Reversal design: A single case design in which the treatment is introduced after a baseline period and then withdrawn during a second baseline period. It may be extended by adding a second introduction of the treatment. Sometimes called a withdrawal design.
Sequential method: A combination of the cross-sectional and longitudinal designs to study developmental research questions.
Single case experimental designs: Research designs in which the effect of the independent variable is assessed using data from a single participant.
Testing effects: A threat to internal validity in which taking a pretest changes behaviour without any effect on the independent variable.
Bar graph: Using bars to depict frequencies of responses, percentages, or means in two or more groups.
Central tendency: A single number or value that describes the typical or central score among a set of scores.
Cohenâ€™s d: An standardized calculation of effect size that is appropriate for two-group experimental designs.
Correlation coefficient: An index of how strongly two variables are related to each other.
Criterion variable: The outcome variable that is being predicted in a multiple regression analysis.
Descriptive statistics: Statistical measures that describe the results of a study; descriptive statistics include measures of central tendency (i.e. mean), variability (i.e. standard deviation), and correlation (i.e. Pearson r).
Effect size: The extent to which two variables are associated. In experimental research, the magnitude of the impact of the independent variable on the dependent variable.
Frequency distribution: An arrangement of a set of scores from lowest to highest that indicates the number of times each score was obtained.
Frequency polygons: A graphic display of a frequency distribution in which the frequency of each score is plotted on the vertical axis, with the plotted points connected by straight lines.
Histogram: A type of graph used when the variable on the x-axis is continuous. A key feature is that the bars touch, unlike bar graphs.
Mean: A measure of central tendency, obtained by summing scores and then dividing the sum by the number of scores.
Median: A measure of central tendency; the middle score in a distribution of scores that divides the distribution in half.
Mode: A measure of central tendency; the most frequent score in a distribution of scores.
Multiple correlation: A correlation between one variable and a combined set of predictor variables.
Multiple regression: An extension of the correlation technique; analysis that models the extent to which one or more predictor variables is related to one criterion variable.
Partial correlation: The correlation between two variables with the influence of a third variable statistically controlled for.
Pearson product-moment correlation coefficient: A type of correlation coefficient used with interval and ratio scale data. In addition to providing information on the strength of relationship between two variables, the Pearson product-moment correlation coefficient indicates the direction (positive or negative) of the relationship.
Pie chart: Graphic display of data in which frequencies or percentages are represented as « slices » of a pie.
Predictor variable: The variable used to predict changes in the criterion (or outcome) variable in a multiple regression analysis.
Regression equations: Mathematical equations that allow prediction of one behaviour when the score on another variable is known.
Restriction of range: Occurs when the full set of a variableâ€™s possible values are not sampled, which can lead to incorrect inferences about that variable and its relationship to other variables.
Scatterplot: A graph in which individual scores are plotted based on their x-y coordinates; used to illustrate the relationship between two variables.
Squared correlation coefficient: A correlation coefficient (i.e. Pearson r) that has been multiplied by itself; can be interpreted as the proportion of variance shared between the two variables.
Squared multiple correlation coefficient: In multiple regression, the proportion of variance in the criterion that can be explained by that set of predictors combined.
Standard deviation: The average deviation of scores from the mean (the square root of the variance)
Variability: The amount of dispersion of scores about some central value.
Variance: Any event, situation, behaviour, or individual characteristic that varies that has at least two values.
Alpha level: In a statistical analysis, the maximum probability that a result â€“ having been declared significant by exceeding this value â€“ has actually come from the null hypothesis sampling distribution. It is usually set at .05
Analysis of variance (F test): A statistical significance test for determining whether two or more means are significantly different; also known as analysis of variance (ANOVA). F is the ratio of systematic variance to error variance.
Conclusion validity: The construct validity of a measure is assessed by examining whether groups of people differ on the measure in expected ways.
Degrees of freedom (df): A concept used in tests of statistical significance; the number of observations that are free to vary to produce a known outcome.
Error variance: Random variability in a set of scores that is not the result of the independent variable. Statistically, the variability of each score from its group mean.
Inferential statistics: Statistics designed to determine whether results based on sample data are generalizable to a population.
Null hypothesis: The hypothesis, used for statistical purposes, that the variables under investigation are not related in the population, that any observed effect based on sample results is due to random error.
Power: The probability of correctly rejecting the null hypothesis.
Probability: The likelihood that a given event (among a specific set of events) will occur.
Research hypothesis: The hypothesis that the variables under investigation are related in the population â€“ that the observed effect based on sample data is true in the population.
Sampling distribution: A frequency distribution of the values of a statistic that would be obtained if a researcher took an infinite number of samples of a particular size, conducted the same study, and calculated the same statistic for each one. Used in inferential statistics to evaluate the likelihood of a given result if only chance is operating.
Statistically significant: Rejection of the null hypothesis when an outcome has a low probability of occurrence (usually .05 or less) if, in fact the null hypothesis is correct.
Systematic variance: Variability in a set of scores that is the result of the independent variable; statistically, the variability of each group mean from the grand mean of all participants.
T test: A statistical significance test used to compare differences between means.
Type I error: An incorrect decision to reject the null hypothesis when it is true.
Type II error: An incorrect decision to accept the null hypothesis when it is false.
Conceptual replication: Replication of research using different procedures for manipulating or measuring the variables.
Exact replication: Replication of research using the same procedures for manipulating and measuring the variables that were used in the original research.
Literature review: A narrative summary of the research that has been conducted on a particular topic.
Meta-analysis: A set of statistical procedures for combining the results of a number of studies in order to provide a general assessment of the relationship between variables.
Replication: Repeating a research study; a way of increasing confidence that the results of a single study represent the truth.

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Number of cards 171

Created By bobbobbob