Research & Stats Flashcards

1
Q

Why would sample means vary in a sampling distribution

A

sampling error (which is a type of random error)

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2
Q

The central limit theorem says that the sampling distribution will increasingly approach a normal shape as ___ increases, regardless of the shape of the population distribution of scores

A

sample size

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3
Q

How can you reduce beta (the probability of making a Type II error)

A

increasing statistical power

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4
Q

the larger alpha, the ___ the power

A

greater

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5
Q

which type of test has more power (parametric or nonparametric)

A

parametric

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6
Q

what type of data are needed for parametric tests

A

interval or ratio

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7
Q

which is non-parametric:
t-test
anova
chi-square

A

chi-swuare

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8
Q

if the population is homogeneous, does that increase or decrease power

A

increase

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9
Q

Bayesian analysis combines information from data collected in the current study with what?

A

previous information about that parameter

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10
Q

the extent to which it is possible to derive an accurate conclusion about the cause-effect relationship between a study’s independent and dependent variables

A

internal validity

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11
Q

The extent to which it is possible to generalize that conclusion beyond the conditions of the current study

A

external validity

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12
Q

Best ways to control history when it’s due to events that occur outside the context of the study

A

include more than one group
randomly assign participants to different groups

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13
Q

the ____ the study, the more likely its results will be threatened by maturation

A

longer the duration

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14
Q

the best way to control maturation is to

A

include more than one group and randomly assign participants

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15
Q

differential selection is a misnomer because it actually refers to

A

differential assignment of subjects to treatment gorups

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16
Q

statistical regression is also known as

A

regression to the mean

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17
Q

to manage statistical regression, you can either not include only extreme scorers OR have more than one group and ___

A

ensure that they are equivalent in terms of extreme scorers at the beginning

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18
Q

what can the solomon four-group design help with

A

testing threats

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19
Q

this threatens a study’s external validity whenever participants respond differently to the independent variable during a study than they would normally respond

A

reactivity

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20
Q

cues that inform participants of what behavior is expected of them.

A

demand characteristics

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21
Q

what does the latin square design do

A

counterbalances treatment order

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22
Q

best way to control selection-treatment interaction

A

randomly select subjects from the population

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23
Q

qualitative approach with a goal “to derive a general, abstract theory of a process, action, or interaction grounded in the views of the participants in a study”

A

grounded theory

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24
Q

gain an in-depth understanding of the “lived experience” of participants – i.e., “how they perceive it, describe it, feel about it, judge it, remember it, make sense of it, and talk about it with others”

A

phenomenology

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25
qualitative "method for identifying, analysing, and reporting patterns (themes) within the data
thematic analysis
26
consists of a single baseline phase and a single treatment phase
AB design
27
a category of single-subject design when at least one additional baseline phase is added
reversal or withdrawal design (e.g., ABA, or ABAB)
28
begins with a baseline phase which is followed by a treatment phase, withdrawal of the treatment during a second baseline phase, and then application of the same treatment during the second treatment phase
ABAB design
29
the independent variable is sequentially applied across different "xxx" which can be different behaviors, tasks, settings, or subjects
baselines - in the multiple baseline design
30
what is the advantage of the multiple baseline design over the reversal designs
once the IV is applied, it does not have to be withdrawn
31
a study that includes two or more groups of subjects, with each group being exposed to a different level of the independent variable is what category of experimental research
between-subjects design
32
a study where each participant is exposed to some or all levels of the independent variable, with each level being administered at a different time is what category of experimental research
within-subjects design
33
what type of experimental design is a time-series design
within-subjects
34
a group version of the single-subject AB design and involves measuring the dependent variable at regular intervals multiple times before and after the independent variable is administered so that all participants act as both the control (no treatment) and treatment groups
time-series design
35
a study includes at least two independent variables, with at least one variable being a between-subjects variable and another being a within-subjects variable
mixed design
36
when a research design includes two or more independent variables, what type of design is it
factorial
37
in a factorial design, the effect of one independent variable on the dependent variable
main effect
38
in a factorial design, the combined effect of two or more independent variables on the dependent variable.
interaction effect
39
requires the random selection of the sample from the population, which helps ensure that members of the sample are representative of the population
probability sampling
40
in a negatively skewed distribution, the ___ has the lowest value, the ___ the middle, and the ___ the highest
mean median mode
41
it's easier to determine which chi-square (single-sample or multiple-sample) test to use if you substitute the word "xx" for sample
variable
42
use this test when a study includes one independent variable that has two levels and one dependent variable that’s measured on an interval or ratio scale
t-test
43
is used to compare an obtained sample mean to a known population mean
t-test for a single sample
44
is used to compare the means obtained by two groups when subjects in the groups are unrelated – e.g., when subjects were randomly assigned to one of the two groups
t-test for unrelated samples
45
is used to compare two means when there’s a relationship between subjects in the two groups
t-test for related samples
46
is used when a study includes one independent variable that has more than two levels and one dependent variable that’s measured on an interval or ratio scale
one-way ANOVA
47
numerator of the F-ratio
mean square between
48
MSB includes treatment effects plus
error
49
denominator of the F-ratio
mean square within
50
mean square within measures variability due to
error only
51
If the F-ratio is >1, this suggests that
the IV had an effect on the DV
52
an extension of the one-way ANOVA that’s used when a study includes more than one independent variable
factorial ANOVA
53
another name for mixed ANOVA
split-plot ANOVA
54
a type of ANOVA used when the data included at least one between-subjects IV and at least one within-subjects IV
mixed or split-plot ANOVA
55
ANOVA that is used to control the effects of an extraneous variable on the DV by including it as an IV and determining its main and interaction effects on the DV
randomized block ANOVA
56
used to control the effects of an extraneous variable on a DV by statistically removing its effects from the DV
ANCOVA
57
the appropriate statistical test 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
MANOVA
58
correlation coefficient used when data on both variables are reported as ranks
Spearman rho
59
correlation coefficient used when both variables are continuous and the relationship is linear
Pearson r
60
correlation coefficient used when both variables are continuous and the relationship is nonlinear
eta
61
correlation coefficient used when one variable is continuous and the other is a true dichotomy
point biserial
62
correlation coefficient used when one variable is continuous and the other is an artificial dichotomy
biserial
63
correlation coefficient used when both variables are nominal
contingency
64
the appropriate technique when two or more continuous predictors will be used to estimate status on two or more continuous criteria
canonical correlation
65
the appropriate technique when two or more predictors will be used to estimate status on a single criterion that’s measured on a nominal scale
discriminant function analysis
66