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Research and Program Evaluation Flashcards

1
Q

cohen’s d effect size

A

(ES): used to gauge how strong a relationship exists

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2
Q

Kurt Lewins concept of action research

A

goes beyond advancing knowledge and works to improve situation. Bridges gap between research and application.

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3
Q

experiement

A

most valuable type of research, used to discover cause and effect. Must have treatment controlled via experimenter and random assignments used in groups.

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4
Q

quasi experiment

A

researcher uses pre-existing groups, so ind variable cannot be altered. Cannot state with any degree of stat confidence that the ind variable caused dep variable

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5
Q

ex post factor study

A

“after the fact”. Correlational study using pre-exisiting groups.
Internal validity: whether depp variable (DV) were truly influenced by experimental ind variables (IV).

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6
Q

external validity

A

whether the experimental research results can be generalized to larger populations (i.e. other ppl, settings, conditions)

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7
Q

factor analysis

A

stat procedure htat uses important or underlying factors in an attempt to summarize a lot o variables. Ex: a test that measures a counselors ability using 3 most imp variables or factors that make an effective helper even though there are hundreds of factors that might exist.

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8
Q

chi square

A

stat measure that tests whether an actual distr. Differs sig. From expected theoretical dist

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9
Q

parsimony

A

interpreting results in simplest way. Strive for parsimony in research (looking for least complex explanation)

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10
Q

occams razor

A

experimenters will interpret results in simplest manner (interchangable with parsimony)

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11
Q

conway lloyd morgan

A

english psychologys, physiologist. Created principle of economy in 1894 cannon

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12
Q

william of occam

A

14th cent. Philosopher, early behaviorists adhere closely to occams razor

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13
Q

bubbles

A

refers to flaws in research

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14
Q

contaminating variable

A

variable that enters experiment that is not being controlled by researcher (aka confounding variable)

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15
Q

basic research

A

research conducted to advance understanding of theory

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16
Q

appplied research

A

aka action research or experience-near research. Conducted to advance knowledge of how theories skills techniques can be used in practical application.

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17
Q

variable

A

behavior or circumstance that can exist on at least 2 levels or conditions. Factor that varies or is capable of change.

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18
Q

ind var IV

A

var. That researcher manipulates or wishes to experiment with

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19
Q

dep var. DV

A

expresses outcome of data

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20
Q

discrete var

A

categories

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21
Q

continuous var.

A

has range

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22
Q

causal comparitive design

A

true experiment apart that the groups were not randomly assigned.

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23
Q

code of ethics for researchers

A

inform subjects of risks, remove negative after effects from research, allow subjects to withdraw at any point, protect confidentiality, present results in accurate and not misleading format, should only use techniques you are trained in.

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24
Q

control group

A

do not receive IV

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25
Q

experimental group

A

does receive IV

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26
Q

true experiment

A

need at least 30 subjects for correlational study and 100 subjects for survey.

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27
Q

organismic IV

A

a variable in which researcher cannot control yet exists such as height weight or gender.hy

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28
Q

hypothesis testing

A

Assoc. With work of RA Fisher. statement with can be tests regarding relationship of IV and DV.

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29
Q

null hyp

A

will not be sig. Difference between exper. Group and control group

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30
Q

exper hyp

A

a difference is evident between control group and experimental group. Aka affirmative hypothesis/alternative hypothesis.

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31
Q

corelational research

A

does not use IV. just comparing 2 things that already exist.

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32
Q

descriptive stat

A

describe data such as mean medium mode

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33
Q

inferential stat

A

infer something about pop.

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34
Q

percentile rank

A

descriptive stat that tells counselor what % of cases fell below a certain level (don’t confuse with percentage scores)

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35
Q

percentage scores

A

another way of stating raw score

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36
Q

test of significance

A

test used to determine whether difference in groups scores are significant or just due to chance.

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37
Q

t test

A

test of stat significance used when an experiment or study is measuring the difference between 2 groups

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38
Q

ind group comparison design

A

study in which 2 groups are ind. Of each other in that 1 group doesnt influence the other group

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39
Q

repeated measures comparison design

A

if researcher measures same group without IV and then with IV. aka between subjects design.

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40
Q

P (in test for significance)

A

Probability. The lower the number, the more that chance factors are rules out.

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41
Q

Parameter

A

a value obtained from a population

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42
Q

Statistic

A

a value drawn from a sample

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43
Q

Correlation coefficient

A

the degree or magnitude of relationship between two variables. Abbreviated using r. Makes a statement regarding the association of two variables and how a change in one is related to the change in another. Range from 0.00 to 1.0. A positive correlation is not stronger. The minus sign describes that as one goes up the other goes down.

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44
Q

Positive correlation

A

both variables change in same direction

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45
Q

Negative correlation

A

Inverse association of variables

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46
Q

Biserial correlation

A

one variable continuous and other is dichotomous

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47
Q

Level of significance synonyms

A

alpha level, probability, confidence level, cutoff point or “where one draws the line”

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48
Q

Accepted level of significance/alpha level/probability/or confidence level in social science

A

0.05 or lower

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49
Q

When setting alpha

A

very stringent alpha is best and larger sample size helps reduce chances for error. More stringent alpha decreases alpha errors but increase beta error

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50
Q

p=0.05 means

A

5% chance that the difference between control and experimental group is due to chance factors. Aka 95% confidence interval. Differences truly exist, the experiment will obtain the same results 99 times out of 100.

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51
Q

Type 1 error

A

alpha error. Researcher rejects null hypothesis when it’s true.

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52
Q

Type 2 error

A

beta error. Researcher accepts null hypothesis when it’s false.

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53
Q

Probability of committing type 1 error

A

the level of significance

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54
Q

1 minus beta

A

the power of a statistical test

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55
Q

Power (in statistical testing)

A

connotes a statistical test’s ability to reject correctly a false null hypothesis. Parametric tests have more power than nonparametric statistical tests.

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56
Q

Parametric test

A

used only with interval and ratio data

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57
Q

Type I Type II relationship

A

seesaw (when one goes up, the other goes down)

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58
Q

Increasing sample size

A

will reduce type I and type II errors. Differences revealed using larger sample sizes are more likely to be genuine.

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59
Q

t test

A

testing for sig. difference between two sample groups. `

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60
Q

ANOVA

A

analysis of variance. Used for testing sig. Difference between more than two groups. Yields an f statistic. Table consulted to find critical value of f. If f obtained is higher than that in the table, the null hypothesis is rejected. (one way analysis of variance)

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61
Q

Two-way ANOVA

A

testing two independent variables

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62
Q

MANOVA

A

multivariate analysis of variance for when a study has more than one DV

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63
Q

ANCOVA

A

analysis of covariance. Tests two or more groups while controlling for extraneous values called covariants.more powerful than anova. Ancova helps take out covariates. extraneous values called covariants.

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64
Q

Kruskal-Wallis

A

Used instead of one-way ANOVA when the data are nonparametric.
Wilcoxon signed-rank test - used in place of the t test when the data are nonparametric and you’re testing whether two correlated means differ significantly.

Used when groups are 3 or more

65
Q

Mann-Whitney U test

A

determine whether two uncorrelated means differ sig. When data are unparametric

66
Q

Spearman Correlation or Kendall’s Tau

A

Used in place of Pearson r when parametric assumptions cannot be utilized.

67
Q

Chi-square

A

nonparametic test. Examines whether obtained frequencies are sig. different from expected frequencies.

68
Q

Covary positively

A

two variables vary together

69
Q

Correlation does not mean

A

causal

70
Q

Correlation research does not yield

A

cause-effect data

71
Q

Bivariate

A

when correlational data describe the nature of two variables

72
Q

Multivariate

A

when more than two variables are under scrutiny

73
Q

N = 1 study structure

A

aka case study. Take a baseline of behavior, implement treatment, measure behavior again.

74
Q

Single-blind study

A

the subjects are unaware of the treatment (control or experimental), but researcher is aware

75
Q

Double-blind study

A

the subjects and researchers are unaware of the treatment (control or experimental). Useful to eliminate experimenter effects.

76
Q

AB or ABA

A

time-series design. Rely on continuous measurement.
A - baseline secured
B - intervention implemented
A - outcome examined

77
Q

Multiple-baseline design

A

when a researcher employs more than one target behavior

78
Q

Pearson r

A

interval and ratio aka information and referral

79
Q

Spearman rho

A

ends in “o” as in ordinal

80
Q

Skewed distributions

A

not normal curve. Left and right sides of the curve are not mirror images

81
Q

Mode

A

most frequent score. “Point of maximum concentration”

82
Q

Mean

A

average score aka “x bar” or x̄.

83
Q

Median

A

the middle score when data are arranged from highest to lowest.
Modal score - highest point on the curve

84
Q

Normal distribution - 68% of scores

A

fall within +/- 1 SD of the mean

85
Q

Normal distribution - 95% of scores

A

fall within +/- 2 SD of the mean

86
Q

Normal distribution - 99.7% of scores

A

fall within +/- 3 SD of the mean

87
Q

The greater the SD

A

the greater the spread of scores

88
Q

Bimodal distribution looks like

A

camel’s back with two humps

89
Q

Factorial design

A

can be used when there are two or more independent variables. IVs in factorial designs can be called levels

90
Q

Mean is misleading when

A

the distribution is skewed or there are extreme scores.

91
Q

Solomon four-group design

A

using two control groups. One experimental group and control group are pretested. This allows the researcher to know if results are influenced by pretesting.

92
Q

Positively skewed

A

the tail points to the right (positive side)

93
Q

Negatively skewed

A

the tail points to the left (negative side)

94
Q

Raw score

A

Expressed in theunits by which it was originally obtained.

95
Q

Histogram

A

bar graph

96
Q

Horizontal bar chart

A

when bars are drawn horizontally

97
Q

Double-barred histogram

A

used to compare two distributions

98
Q

X axis

A

aka “abscissa”. Horizontal. used to plot IV scores

99
Q

Y axis

A

aka “ordinate”. vertical. Scale for DV.

100
Q

Abscissa

A

x axis

101
Q

Ordinate

A

y axis

102
Q

Observer effect

A

situation in which a person observing influences or alters the situation

103
Q

Naturalistic observation

A

occurs when clients are observed in a natural setting or situation. Researcher does not intervene.

104
Q

Range

A

measure of variance. The difference between the highest and lowest score. Some statistic books define the range as the highest score minus the lowest score plus 1. Range generally increases with sample size.

105
Q

“Inclusive range”

A

highest score minus the lowest score plus 1

106
Q

“Exclusive range”

A

highest score minus the lowest score

107
Q

Sociogram

A

a graph database that depicts the relationships among individuals in a group in order to map the group’s social network

108
Q

Scattergram

A

aka scatterplot - a pictorial diagram or graph of two variables being correlated

109
Q

John-Henry effect

A

threat to internal validity of experiment. Subjects strive to prove that an experimental treatment that could threaten their livelihood isn’t effective. I.e. counselor educators asked to use computers (worried about computers taking over their jobs) will resist the usefulness of computers by preparing more.

110
Q

Variance

A

the measure of dispersion of scores around some measure of central tendency. Standard deviation squared.

111
Q

z-score

A

same as standard deviation. Also called standard scores.

112
Q

t-score

A

transferred scores. Use a mean for 50 with SD as 10.

113
Q

One tailed t test

A

places rejection area at one end of dist. Aka one directional experimental hypothesis.

114
Q

two-tailed t test

A

placed rejection area at 2 ends of dist. Aka nondirectional experimental hypothesis

115
Q

CEEB

A

college entrance examination board, scores are standardized and scale ranges from 200 to 800 with mean of 500. Use SD of 100. Aka ETS score.

116
Q

Platykurtic distribution

A

looks like upper half of a hot dog, lying on its side over the abscissa. Flatter and more spread of than frequency dist.

117
Q

Kurtosis

A

peakedness of a frequency dist.

118
Q

Leptokurtic

A

very tall, thin, peaked.

119
Q

Stanine scores

A

divide dist. into 9 equal intervals.stanine 1=lowest 9 and stanine 9=highest. 5 is mean.

120
Q

4 basic measurement scales

A

nominal, ordinal, interval, ratio. SS stevens came up with these groups. Memory device: NOIR.

121
Q

Nominal

A

strictly quantitative scale, simplest, distinguish logically separated groups. No 0 point, and doesn’t indicate order.

122
Q

Ordinal scale

A

variables. Provides relative placement or standing but does not delineate absolutes. (ordinal=order)

123
Q

interval

A

has numbers scaled at equal distances but has no absolute 0 point. Most tests used in scores fall into this category. Can add and subtract but no divide or multiply.

124
Q

Ratio scale

A

interval scale with true 0 point. Ratio Measurements are possible. Subtraction, addition, multiplication, division can all be used. Most psych attributes cannot be measured on ratio scale. I.e. time weight height volume distance

125
Q

survey

A

needs at least 100 ppl, needs 50-75% return rate to be accurate. Drawbacks include: low return rate, poor construction, non-random selection of subjects->cannot be representative of population.

126
Q

nocebo

A

placebo with negative effect.

127
Q

Hawthorne effect

A

elton mayo and fritz roethlisberger 1924-1932 at Hawthorne Works. Work production increased with better lighting and worse lighting. If subjects know they are part of an experiment, their performance improves. Aka reactive or reactivity effect (subjects behavior is influenced by presence of researcher)

128
Q

Rosenthal effect

A

aka experimenter expectancy effect. Experimenter knows about experiment and so makes positive impact on subjects.

129
Q

Covariate

A

correlates with the DV. unintended variable that can influence the DV.

130
Q

Statistical regression

A

predicts very high and very low scores will move towards the mean if test is administered again. Based on law of filial regression.

131
Q

Quartile

A

refers to the points that divide dist into fourths. 25th percentile is first quartile

132
Q

Inter-quartile range

A

distance between the 25th and 75th percentiles.

133
Q

Cross sectional study

A

aka syncronic method. Clients are assessed at one point in time

134
Q

Diachronic method

A

longitudinal study. Data are collected at different points in time.

135
Q

Demand characteristics

A

relates to any bit of knowledge correct or incorrect that a subject in the experiment is aware of that will influence their behavior. These characteristics can confound an experiment.

136
Q

Summative

A

at end. Used to assess final formal product

137
Q

Pygmalion effect

A

experimenter falls in love with own hypothesis and so experiment becomes self fulfilling prophecy

138
Q

Ahistoric therapy

A

any model that focuses on here and now rather than the past

139
Q

Multiple treatment interference

A

if a subject receives more than one treatment it becomes hard to discern which treatment caused the results.

140
Q

ERIC

A

educational resources information center. Resource bank of scholarly literature.

141
Q

SPSS

A

Statistical package for the social sciences. Software program that helps with computing statistics.

142
Q

Random sampling

A

each subject has same prob. Of being selected. Selection of 1 subject doesnt affect selection of another.

143
Q

Stratified sampling

A

looking for a special characteristic to be represented or “stratum”. Stratification variable in sample should mimic pop at large. Ex: if 20% of rogerian counselors are AA than 20% of sample should have AA counselors.

144
Q

Quota sampling

A

type of stratified sampling. Where specific number of cases are necessary from each stratum.

145
Q

Cluster sampling

A

used when nearly impossible to find list of entire population. Uses existing sample or cluster of people or selects a portion of overall sample. Wont be as accurate as random sample.

146
Q

Horizontal sampling

A

occurs when researcher selects subjects from single socio economic class.

147
Q

Vertical sampling

A

converse of above when 2 or more socio economic classes are utilized.

148
Q

Snow-ball sampling

A

aka chain-referral sample. Uses subjects to find more subjects.
Systematic sampling: take every nth person. Choose list of people, pick every nth (i.e. every 3rd, every 10th etc.).

149
Q

Sampling error

A

what happens when sample does not mimic population.

150
Q

Axiom

A

universally accepted idea needing no additional proof

151
Q

Operational definition

A

outline of procedure esp. Of research so that other researchers can replicate experimental procedure. Must be specific.

152
Q

Non parametric tests

A

distribution free tests. Some examples include mann whitney u-test, wilcoxon signed-rank test for matched pairs, solomon and kruskal-wallis h test.

153
Q

Matched design

A

subjects are matched in regards to any variable that could be correlated with DV.

154
Q

Unmatched or uncorrelated groups

A

aka independent groups

155
Q

Inductive logic

A

research goes from specific to general

156
Q

Deductive

A

reduces general to specific

157
Q

Impaired

A

deterioration in the ability to function as a counselor

158
Q

Within subjects design

A

when 2 or more levels of IV are administered to each subject. Each subject acts as his/her own control.

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