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1
Q

Independent Variables

A

variable believed to affect or alter status on another variable , viewed as the treatment of intervention

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2
Q

Dependent Variables

A

status on that variable seems to depend on the status on another variable

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3
Q

Moderator Variables

A

affects the strength or direction of the relationship between the independent and dependent variable

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4
Q

Mediator Variables

A

responsible for the observed relationship between variables,

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5
Q

Interval Recording

A

known as interval sampling and time sampling, and involves observing a behavior for a period of time that has been divided into equal intervals ( 30 minutes that divided into 15 second intervals) and recording whether or not the behavior occurs during each interval, useful for studying complex behaviors that have no clear beginning or end, laughing, talking, playing

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6
Q

Event sampling:

A

Event recording, entails observing and recording the behavior each time it occurs, recording can take several forms including using a precoded checklist or recording the times when the behavior began and ended, studying behaviors that occur infrequently, have a long duration

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7
Q

True vs Quasi Experimental Research

A

True Experimental: provides amount of control necessary to conclude that observed variability in a dependent variable is caused by variability in an independent variable, able to randomly assign subjects to different treatment groups
Quasi Experiment: investigating the effects of an independent variable on a dependent variable, but does not provide an investigator with the same degree of experimental control, cannot control assignments of groups

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8
Q

Random assignment vs random selection

A

random assignment helps ensure that any observed differences between groups on the dependent variable are actually due to the effects of the independent variable and refers to way subjects are assigned to different levels of the IV,
Random selection- way subjects are selected from the population and enables the investigator to generalize his or her findings from the sample to the population

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9
Q

Simple Random Sampling

A

when using this method, every member of the population has an equal chance of being included in the sample, and selection of one member from the population has no effect on the selection of another member, reduces probability that the sample will be biased in some way

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10
Q

Stratified Random Sampling

A

when population of interest varies in terms of specific strata that are relevant to the resarch hypothesis, ensure that each stratum is represented in the sample, dividing population into appropriate strata, random selecting subjects from each strata, such as age, gender, education, ses,

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11
Q

Cluster Sampling

A

using simple or statified sampling to select units or clusters rather than individuals and including all individuals in the selected unit or random selecting indiividuals from each unit

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12
Q

Random Error

A

experimental research helps an investigator minimize the effects of random fluctations in subjects, conditions, investigator can make sure that subjects do not become fatigued, setting is free of distractions

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13
Q

Random assignment

A
  • can equalize the effects of known and unknown extraneous variables by randomly assigning subjects to different levels of the IV
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14
Q

Matching

A

match subjects in terms of their status on the extraneous variable and then randomly assign to a treatment group, matching is useful when the sample size is too small to guarantee that random assignment will equalize groups

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15
Q

Blocking

A

controlled by using it in the study as an additional independent variable so its effects on the dependent variable can be analyzed, grouped on the basis of their status on the extraneous variable and subjects in each block are then randomly assigned to treatment groups

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16
Q

Statistical Control

A

when an investigator has information on each subjects status or score on an extraneous variable, he or she can use the ANCOVA to remove any variability in the dependent variable that is due to the extraneous variable

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17
Q

Internal Validity

A

when it allows an investigator to determine if there is a casual relationship between IV and DV, internal validity is threatened when cannot control effects of an extraneous variable, minimize random error, and maximize the effects of the IV

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18
Q

Maturation

A

refers to any biological or psychological change that occurs within subjects during the course of the study as a function of time, is not relevant to the research hypothesis, and affects the status on most or all subjects on the dependent variable . fatigue, boredom, hunger

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19
Q

History;

A

threatens a studys internal validity when an external event affects the status of subjects on the dependent variable, more likely to be a problem when there is only one group, an event occurs at the same time the independent variable is applied

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20
Q

Statistical Regression

A

threat to a study’s internal validity whenever the method used to assign subjects to treatment groups results in systematic differences between the groups at the beginning of the study.

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21
Q

Selection

A

when groups are not equal, selection can act alone or can interact with other factors to threaten a studys internal validity,

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22
Q

External Validity

A

when its results can be generalized to other people, settings or conditions,, external validity is always limited by its internal validity

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23
Q

Pretest Sensitization

A

administration of a pretest can sensitize subjecs to the purpose of the research and alter their reaction to the IV. when the results have been contaminated , they cannot be generalized to ppl who have no been pretested,

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24
Q

Solomon Four Square-

A
  • which allows an investigator to measure the impact of pretesting of both external and internal validity, pretest is treated as an additional IV
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25
Q

Reactivity/Demand Characteristics

A

participants may respond to an IV in a particular way because they know their behavior is being observed, when reactivity happens, results cannot be generalized to conditions where reactivity is not present

Demand Chacteristics: cues in the experimental setting that inform subjects of the purpose of the study or suggest what behaviors are expected of them.

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26
Q

Multiple Treatment Interference/Counterbalancing

A

Study involves exposing subjects to two or more levels of an IV, the effects of one level of the IV can be affected by previous exposure to another level.
Can be controlled by using a counterbalanced design in which different subjects receive the levels of the IV in a different order
*Latin square design is one type of counterbalanced design and involves administering each level of hte IV so it appears the same number of times in each position

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27
Q

Between groups designs

A

effects of different levels of an independent variable are assessed by adminstering each level to a different group of subjects and comparing the status or performance of the groups on the DV. *simplest includes two groups that receive a different level of the IV

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28
Q

Within Subjects Design

A

all levels of theIV are adminstered sequentially to all subjects,
simple group time series design- effects of a a reamtnet are evaulated by measuring the DV several times at regular intervals before and after the treatment is applied

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29
Q

Mixed Design

A

combines between group and within subjects design by including at least one between groups IV and one within subjects IV
*common in studies involving measuring the DV across trials of time

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30
Q

Factorial Design

A
  • when a study includes two or more IVS, provides more thorough information about the relationships among variables by allowing an investigator to analyze the main effects of each IV as well as the interaction between IV.
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31
Q

Main and interaction effects

A

Main effect- effect of one IV on the DV, disregarding the effects of all other independent variables.
Interaction- refers to the effects of two or more IV’s considered together and occurs when the effects on an IV differ at different levels of another IV.

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32
Q

Single Subject Designs

A

includes at least one baselines ( no treatment) phase and one treatment phase
the DV is measured repeatedly at regular intervals throughout the baseline and tx phases, repeated measure helps control any maturational effects that migh otherwise threaten the studys internal validity

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33
Q

AB Design

A

includes a single baseline( A) and a single treatment ( B) , dependent variable is measured at regular intervals during both phases

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34
Q

Reversal ABA, ABABA designs

A

more than one baseline and treatment, provide additonal control over potential threats to a studys internal validity. when an ABAB design is used, is status on the DV returns to the intitial baseline during the second A phase, and then to its previous treatment level during the second B phase , an investigator can be certain that any observed change in the DV is due to the IV
*considered inappropriate when withdrawl of a treatment during the course would be unethical

35
Q

Multiple Baseline

A

does not require withdrawing a treatment during the course of the study, but applying sequential different behaviors of the same subject, to the same subject ind different settings to the same subject on different tasks

36
Q

Nominal Scale

A

divides variables into unordered categories, do not provide information on the order of the catergories, religion, political affiliation, place of birth

37
Q

Ordinal Scale

A

divides observations into categories but also provides information on the order of those categories
Ratings and ranks on a likert scale are examples or ordinal scale scores

38
Q

Interval Scale

A

property of order as well as property of equal intervals between sucessive points on the scale, scores on standardized IQ tests considered to represent an interval scale

39
Q

Ratio Scale

A

properties or order and equal intervals as well as an absolute zero point which measn that a score of 0 indicates a complete absence of the characteristic being measured

40
Q

Normal Curve

A

symmertrical, bell shaped, and defined by specific mathamtical formula,

41
Q

Areas under the normal curve

A

Leptokurtic- more peaked than the normal distribution,
Platykurtic- when distribution is flatter
Mesokurtic- normal curve

42
Q

Positively vs Negatively Skewed Distribution

A

Positvely Skewed- most of the scores are in the negative low score side of the distribution and the positive tail is extended because of the presence of few high scores
Negatively Skewed distribution- most scores are located in the positive high end side of the distrbution and the negative tail is extended due to the presence of few low scores

43
Q

Mode

A

score or catergory that occurs the most frequently in a set of data

44
Q

Median

A

score that divides a distribution in half when the data that has been ordered from low to high, when a distrubution has a odd number of observations, the median is equal to the middle of observations

45
Q

Mean

A

is the average

46
Q

Range:

A

calculated by subtracting the lowest score from the highest score

47
Q

Standard Deviation

A

calculated by taking the square root of the variance which converts it to the same unit of measurement as the orginal score,

48
Q

Sampling Distribution of the Mean

A

is the distrubution of sample means that would be obtained if an infinite number of equal size samples were randomly selected from the population and the mean for each sample was calculated

49
Q

Retention and Rejection regions

A

Retention- region of likely values lies in the central portion of the sampling distribution and consists of the values that are likely to occur as a consequence of sampling error only
Rejection- region of unlikely values lies in one or both tails of the sampling distributions and consists of the values that are likely to occur as a consequence of sampling error only

50
Q

Areas under the normal curve-

A

when a disturbition is normal 68.26% of the scores fall between plus or minus 1 of the standard deviation, 95.44% fall between plus 2 and minus 2, and 99.72 fall between plus 3 and minus 3.

51
Q

Null Hypothesis

A

stated in a way that implies that the independent variable does not have an effect on the dependent variable

52
Q

Alternative Hypothesis

A

states the opposite of the null hypothesis and implies that the independent variable does have an effect

53
Q

Parametric Tests

A

include the t test are used to evaulate hypotheses about population means, variances or other parameter, tests are appropriate only when the variable of interest has been measured on an interval or ratio scale and when certain assumptions about the population distrubution are met.

54
Q

Nonparametic Tests

A

are used to analyze data collected on variables that have been measured on an nominal or ordinal scale , used to evaulate hypotheses in the shape of a distrubution rather than the distrubutions mean variance or other paramter, such as the chi square test, Mann Whitney U test,

55
Q

Single sample Chi Square test

A

also known as the goodness of fit test-

56
Q

Multiple Sample Chi Square Test

A

is used when a descriptive or experimental study that includes two or more variables and the data can be analyzed are the frequency of observations in each category

57
Q

t test for single sample

A

used when a study includes only one group and the group(sample) will be compared to a known population mean

58
Q

t test for independent samples

A

appropriate statical test when a study includes two independent groups and the means of the two groups will be compared

59
Q

t test for correlated samples

A

used when the two means to be compared have come from correlated groups , it is the appropriate test for a study using a within subjects design in which a single group of subjects wil be compared to itself before and after the IV has been applied.

60
Q

One way ANOVA

A

used when a study includes one IV and two or more independent groups and one DV that is measured on an interval or ratio scale. divdies the total sum of swuares into a between groups and a within group sum of squares

61
Q

one way ANOVA - F ratio-

A

the sum of squares are converted to mean squares by diving each sum of squares by the appropriate degrees of freedom, the degrees of freedom are used not only to identify the crucial value

62
Q

Factorial ANOVA

A

is an extension of the one way ANOVA and is used when a study includes two or more independent variables.

63
Q

Randomized block ANOVA

A

type of factorial /ANOVA that is employed when blocking has been used to control an extraneous variable, it involves treating the extraneous variable as an independent variable so that its main and interaction effects can be spastically analyzed , increases stastical power by reducing within group variability

64
Q

Analysis of Covariance ANCOVA

A

combines the analysis of variance with regression analysis and allows an investigator to control an extraneous variable by stastically removing the portion of variability in the dependent variable that is due to the extraneous variable , removing the effects of an extraneous variable the ANCOVA reduces wihin group variability

65
Q

Mixed( split plot) ANOVA

A

appropriate test for studies using a mixed design in which at least one IV is a between groups variable and one IV is a within subjects variable

66
Q

Trend Analysis

A

used when the study involves one or more quanitative independent variables, and the researcher wants to evaluate the shape or form of the relationship between the independent and dependent variable , results indicate whether or not there is a statically significant linear or nonlinear relationship between the variables

67
Q

Multivariate Analysis of Variance MANOVA

A

used when a study includes one or more independent variables and two or more dependent variables that are each measured on an interval or ratio scale, it allows an investigation to simulanteounsly assesses the effects of the independent variable on all of the dependent variables and helps control the experimentwise error

68
Q

Cohen’s d

A

is a measure of the difference between two groups in terms of standard deviation units, calculated by subtracting the mean of one group from the mean of the other group and dividing the result by a pooled standard deviation for the two groups

69
Q

Eta squared

A

indicates the percent of variance in the outcome variables that is accounted for by variance in the treatment

70
Q

Pearson R

A

interval or ratio correlation coefficent

71
Q

Spearman Rho

A

rank ordered correlation coefficent

72
Q

Point Biseral

A

True dichotomoy ( male/female) and interval or ratio

73
Q

Eta

A

interval or ratio, used when the relationship between variables is nonlinear

74
Q

Degree of Association

A

a correlation coefficent can be interpreted directly in terms of degrees of association , the closer the coefficent is to either to -1.0 to 1.0 the stronger the association between variables, the closer it is to 0, the weaker the association

75
Q

Shared Variability

A

when a correlation coefficent represents the degree of association between two different variables, it can be squared to obtain a coefficent of determenation , indicates the proportion of variability in Y that is explained by or accounted for by variability in X.

76
Q

Regression Analysis

A

goal is to use a predictor to predict or estimate performance on a criterion, the technique that allows such predictions to be made when there is one predictor X and one criterion Y

77
Q

Mutiple Regression

A

appropriate multivariate technique when two or more continuous or discrete predictors will be used to predict status on a single continuous criterion, use of multiple regression is based on the assumption that the relationship between variables is linear

78
Q

Multicollinearity

A

a high correlation with two or more predictors *not desirable

79
Q

Cross Validation/Shrinkage

A

size of the correlation coefficent tends to shrink and the predictive accuracy of the regression equation decreases
Shrinkage- occurs because the regression weights which are used in the calculation of R as ell as in the regression equation, greatest when sample is mall, and number of predictors is large

80
Q

Discriminant Function Analysis

A

discriminant analysis and is the appropriate technique when two or more continuous predictors will be used to predict or estimate a persons status or a single discrete criterion

81
Q

Path Analysis

A

can be considered an extension of mutiple regression, translating the theory about the casual relationships among a set of variables into a path diagram

82
Q

LISREL

A

linear structural relations anaylsis- can be used when a casual model includes recursive and non recurive paths, takes into account the latent traits

83
Q

Cluster Analysis

A

used to group people or objects into a smaller number of mutually exclusive or exhaustive subgroups based on their similarities,

Clinical Psychology (7 decks)

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