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EPPP 1
Stats & Research Design
| Question | Answer |
|---|---|
| The systematic study and investigation of a phenomenon in order to reveal, analyze, and establish facts, principals, and theories. | Research |
| This kind of research is conducted to obtain a holistic description of the quality of relationships, actions, situations, or other phenomena. | Qualitative research |
| Participants and nonpartisan and observation, interviews, and document analysis and strategies used by this kind of research? | Qualitative research |
| This kind of research is conducted to obtain numerical data on variables | Quantitative research |
| Makes use of empirical methods and statistical procedures, emphasizes prediction, generalizability, and causality, and is primarily deductive | Quantitative research |
| Also called descriptive research and is conducted to collect data on variables rather than to test hypotheses about the relationships between them. | Non experimental |
| Correlation all research, archival research, case studies, and surveys are ordinarily... | Non experimental |
| This kind of research is conducted to test the papa sees about the effects of one or more independent variables on one or more dependent variables | Experimental research |
| And the characteristic, behavior, event or other phenomenon that is capable of varying or existing at least two different states conditions or levels | Variable |
| When a characteristic is restricted to a single state or condition | Constant |
| A variable that is believed to affect or alter status on another variable | Independent variable |
| When status on a variable seems to depend on status on another variable | Dependent variable |
| Treatment or intervention and is symbolized with the letter X | Independent variable |
| The ___________ is considered the outcome of the treatment | Dependent variable |
| It is measured by pre tests and post tests and is symbolize with the letter Y | Dependent variable |
| The type of content analysis used by psychologists interested in the content of prophecies that underlie problem solving and other complex tasks and involves asking is subject to think aloud while solving the problem | Protocol analysis |
| Observing a behavior for a period of time that has been divided into equal intervals and recording whether or not the behavior occurs during each interval | Interval recording |
| Especially useful for studying complex interactions and behaviors that had no clear beginning or end such as laughing talking or playing | Interval recording |
| Observing a behavior each time it occurs and is good for studying behaviors that occur infrequently, they have a long duration, or that leave a permanent record or other product. | Event sampling |
| An alternative to behavioral sampling and is used when the goal of the study is to observe the behavior in a number of settings, helps increase the generalize ability of the study's findings. | Situational sampling |
| Entails a coding behavioral sequences rather than isolated behavioral events and is used to study complex social behaviors | Sequential analysis |
| Research can be categorized as ____________ or quantitative | Qualitative |
| Classified as either true experimental or quasi experimental | Experimental research |
| Only this provides the amount of control necessary to conclude that observed variability in a dependent variable is actually cause by variability in an independent variable | True experimental research |
| This helps to ensure that any observed differences between groups on the dependent variable | Random assignment |
| In this type of research and experimenter cannot control the assignment of subjects to treatment groups but instead must use intact or preexisting groups or single treatment group | Quasi experimental research |
| When using this method to every member of the population has an equal chance of being included in the sample and the selection of one member from a population has no effect on the selection of another member reduces probability of bias | Simple random sampling |
| When the population of interest varies in terms of specific characteristics relevant to the hypothesis this can be used to ensure that each stratum is represented in the sample | Stratified random sampling |
| This involves dividing the population into the appropriate strata and randomly selecting subjects from each stratum typical strata include gender, age, education level, SES, and racial ethnic or cultural background | Stratified random sampling |
| This entails selecting units of individuals rather than individuals and either including all individuals in those units in the resource are your randomly selecting individuals from each unit | Cluster Sampling |
| This is useful when it is not possible to identify or obtain access to the entire population of interest | Cluster sampling |
| An investigator wants to choose a research design that does what 3 things | Maximizes variability in the dependent variable that is due to the independent variable, controls variability that is due to extraneous variables, minimizes variability caused by random error. |
| A source of a systematic error | Extraneous were confounding variables |
| If variable that is relevant to the purpose of the research study but confounds the two results because it has a systematic effect on the dependent variable | Extraneous were confounding variable |
| Techniques used to control the effects of extraneous variables: | Random assignment of subjects to treatment groups, holding the extraneous variable constant, matching subjects on extraneous variables, building at the extraneous variable into the study or blocking, statistical control of the extraneous variable |
| Equalizes the effects of all known and unknown extraneous variables that randomly assigning subjects to the different levels of the independent variable Considered the most powerful method of experimental control | Random assignment |
| Can eliminate the effects of an extraneous variable by selecting subjects who are homogenous with respect to that variable. Primary shortcoming is that it limits the generalize ability of the research results. | Holding the extraneous variable constant |
| Ensures the groups are equivalent by matching subjects in terms of their status on that variable and then randomly assign the matched subjects to one of the treatment groups. Particularly useful when the sample sizes too small. | Matching subjects on the extraneous variable |
| Extraneous variable can be controlled by including it in the study as an additional independent variable so that its effects on the dependent variable can be statistically analyzed. | Building the extraneous variable into the study or blocking |
| With information on each subjects status or score on the extraneous variable can use the ANCOVA or analysis of co variance or other statistical techniques to remove variability in the independent variable that is due to the extraneous variable. | Statistical control of the extraneous variable |
| An investigator can make sure the subjects to not become fatigued during the course of the study, that the experimental setting is free from distractions and fluctuations in environmental conditions, and that all measuring devices are reliable | This minimizes the effects of random error |
| A study has this when it allows an investigator to determine if there is a causal relationship Between independent and dependent of variables | Internal validity |
| Threats to internal validity | Maturation, history, testing, instrumentation, statistical regression, selection, attrition, interactions with selection |
| Any biological or psychological change that occurs within subjects during the course of the study as a function of time that is not relevant to the research hypothesis and affects the status of most were all subjects on the dependent variable in a systema | Threat to Internal Validity - Maturation |
| Threatens a studies internal validity when an an external event to systematically affects the status of subjects on the dependent variable | Threat to Internal Validity - History |
| This can threaten the studies internal validity whenever exposure to a test might alter subjects performance on subsequent tests | Threat to Internal Validity - Testing |
| When the accuracy or sensitivity of measuring devices or procedures during the course of the study confound the study's results | Threat to Internal Validity - Instrumentation |
| The tendency of extreme scores on a measure to move request for the mean when the measure is read minister to the same group of people | Threat to Internal Validity - Statistical regression |
| Whenever the method used to assign subjects to treatment groups results in systematic differences between the groups at the beginning of the study | Threat to Internal Validity - Selection |
| When subjects who drop out of one group differ in an important way from subjects who dropped out of other groups | Threat to Internal Validity - Attrition |
| When groups are initially non equivalent, Selection can act alone and or can interact with other factors to threaten the studies internal validity. | Threat to Internal Validity - Interactions with selection |
| When the findings of a research study can be generalized to other people settings and conditions | External validity |
| Used to describe the generalize ability of research results to other people | The population validity |
| The generalize ability of results to other settings | Ecological validity |
| He studies external validity is always limited by | internal validity |
| A high degree of internal validity does not guarantee.... | external validity |
| Four factors that impact and external validity | Interaction between testing and treatment, interaction between selection and treatment, reactivity or reactive arrangements, the multiple treatment interference |
| When a study's results have been contaminated by a pretest sensitization they cannot be generalized to people who have not been protested | Threats to External Validity - Interaction between testing and treatment |
| Often a problem when subjects are volunteers because volunteers tend to be more motivated than on volunteers and consequently it might be more responsive to the IV | Threats to External Validity - interaction between selection and treatment |
| Research participants can respond to an independent variable in a particular way simply because they know their behavior is being observed | Threats to External Validity - reactivity |
| Cues in the experimental setting that inform subjects of the purpose of the study or suggest what behaviors are expected of them | Threats to External Validity - Demand characteristics |
| Can be controlled using deception, unobtrusive measures, or a single or double blind technique. | Reactivity |
| In this blind technique subjects do not know which treatment group they have been assigned to | Single blind technique |
| In this blind technique neither the subjects nor the experimenter know which group subjects have been assigned to | Double blind technique |
| When a study involves exposing each subjects to two or more levels of an independent variable the effects of one level of the independent variable can be affected by previous exposure to another level | Threats to External Validity - Multiple treatment interference |
| Can be controlled by accusing a counterbalance design in which different subjects receive the levels of the IV in a different order | Multiple treatment interference |
| One type of counterbalanced design that involves administering each level of the IV so that it appears the same number of times in each position | The Latin Square design |
| Between – groups designs | Effects of different levels of an independent variable are assessed by administering each level II different group of subjects and then comparing the status or performance of the groups on the dependent variable |
| Whenever a study includes two or more independent variables it is called… | Factorial design |
| The major advantage of a factorial design is that… | It provides more thorough information about the relationships among variables by allowing an investigator to analyze the main effects of each independent variable as well as the interaction between independent variables |
| Main effect | The effect of one independent variable on the dependent variable, disregarding the effects of all other independent variables |
| Interaction effects | Effects of two or more independent variables considered together. Occurs when the effects of an independent variable differ at different levels of another independent variable |
| To determine if there are main effects of each independent variable, it is necessary to calculate the | Marginal means: |
| What is the marginal mean? | Add the mean scores in each column and divide by the number of rows |
| Within – subjects designs | (AKA - repeated measures)All levels of the independent variable are administered sequentially to all subjects. Comparisons of different levels of the eyes the are made within subjects rather than between groups of subjects. |
| The single group timeseries design | A type of within – subjects design. Effects of the treatment are evaluated by measuring the DV several times at regular intervals both before and after the treatment. Internal validity threatened by history. Helps control maturation. |
| A disadvantage of the timeseries and other within subjects designs is… | The analysis of the data can be confounded by autocorrelation; Performance on the post tests is likely to correlate with their performance on the pretests. |
| Next design | Combines between groups and within subjects methodologies. Common in studies measuring the DVD over time or across trials. Time or trials is an additional IV. Considered within subjects variable bc comprsns on DV made within subjects across time or trials |
| Single subject designs | Often used to investigate the effects of an independent variable on the behavior of one subject or small number of subjects. Includes at least one baseline phase and one treatment phase. |
| Most common single subject design | AB design |
| AB design | A single baseline and a single treatment. DV is measured at regular intervals during both phases |
| Reversal designs (ABA, ABAB, Etc.) | NAB design expanded to include more than one baseline phase or more than one baseline and more than one treatment phase. They provide additional control over potential threats to a study's internal validity |
| Multiple baseline design | Used if the reversal design is inappropriate for ethical or practical reasons. Does not require withdrawal of the treatment during the course of the study. Once treatment has been applied to a baseline it is not withdrawn |
| Two types of statistics | Descriptive and inferential |
| Descriptive statistics are used to | Describe and summarize the data collected on a variable or the relationship between variables |
| Inferential statistics are used to | Determine if obtained sample values can be generalized to the population from which the sample was drawn. |
| Continuous variable | Theoretically can take on an infinite number of values on the measurement scale, for example time |
| Discrete variable | Can only assume a finite number of values. For example DSM diagnosis |
| Scales of measurement (4) | Nominal, ordinal, interval, and ratio |
| Nominal scale of measurement | Divides variables into on ordered categories. For example gender, religion, place of birth, eye color.Measure of central tendency: mode |
| Ordinal scale | Mathematically complex. Divides observations into categories,provides information on the order of categ. Likert scales is example of ordinal scale scores. Offers relative order but can't tell how much diff bet scores. Measure of cen tend: mode or median |
| Interval scale | Also has property of order and the property of equal intervals. IQ score. Property of equal intervals makes it possible to perform mathematical operations of addition and subtraction. May have zero point; arbitrary not absolute zero.Meas of cen tend: any |
| Ratio scale | Most mathematically complex. Properties of order, equal intervals, absolute zero point. Score of zero indicates a complete absence of characteristics. Absolute zero allows multiplication and division.Meas of cen tend: any |
| Descriptive techniques include | Tables, frequency distributions, frequency polygons, measures of central tendency, and measures the variability. |
| Frequency polygon | Data set for ordinal, interval, or ratio scale. Scores are recorded on the horizontal axis, while frequencies are coded on the vertical axis |
| Kurtosis | The relative peak goodness, fight or flatness, of the distribution. |
| Leptokurtic | The distribution is more peaked than the normal distribution |
| Platykurtic | The distribution is flatter than the normal distribution |
| Skewed distribution | More than half of the observations fall on one side of the distribution in the relatively few observations fall in the tail on the other side of the distribution |
| Positively skewed distribution | The peak is to the left |
| Negatively skewed distribution | The peak is to the right |
| Measures of central tendency | Convey the maximum amount of information, summarizes the entire set of observations and is typical measure of all the observations. Includes mean, median, mode. |
| Mode (Mo) | The score or category that occurs most frequently in a set of data. Easy to identify. Disadvantage is that it is very susceptible to sampling fluctuations |
| Median (Md) | The score that divides a distribution in half when the data have been ordered from low to high. Advantage: outliers do not affect median. Use in quantitative procedures is limited, serves primarily as descriptive statistic |
| Arithmetic mean (M or X) | The arithmetic average.Least susceptible to sampling fluctuations. Affected by the magnitude of every score in the distribution. |
| Measure of variability | Indicate the amount of heterogeneity or dispersion within a set of scores and include the range, the variance, and the standard deviation. |
| Range | Calculated simply by subtracting the lowest score in the distribution from the highest score. |
| Variance (Mean Square) | Provides a measure of the average amount of variability in a distribution by indicating the degree to which the scores are dispersed around the distributions mean. |
| Standard deviation | Can be interpreted directly as a measure of variability. The larger the standard deviation the greater the dispersion of scores around the distributions mean. |
| A Kappa Coefficient of .95 suggests | a high degree of interrater reliability |
| standard error of the estimate | The average amount of error in prediction |
| the standard error of the mean. | The average amount of error in the group's mean, in relation to the population mean, |
| the standard deviation of the IQ scores | The average amount of spread of IQ scores |
| The standard error of measurement | the average amount of error in each person's IQ score, as measured by the IQ test |
| Soloman Four Group Design | Used to control for the effects of testing. |
| The Kappa Coefficient is used to express | interrater reliability. |
Created by:
bwl200
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