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99 Cards in this Set

  • Front
  • Back
an idea constructed by the researcher to explain observed events (a rational idea that is used to explain a phenomenon); an operational definition (explanatory idea about internal states that generate behavior)
How well the study’s results support the theory or
constructs behind the research; Whether the theory supported by the findings
provides the best available explanation of the
construct validity
How do we maximize construct validity?
The researcher should use clearly stated
definitions and carefully build hypotheses on
solid, well‐validated constructs which have
received support from numerous other
studies; have a clear definition of the constructs of interest; verify that there is a good match between constructs and operations used to represent them
Defined as the degree of confidence that the
inferences about study outcomes based on
statistical tests are correct
statitical conclusion validity
What are the factors affecting validity types?
-measurements must be reliable and valid
-useful measures are sensitive
-useful tests are specific
-should avoid ceiling and floor effects
-researcher bias
refers an effect whereby data
cannot take on a value higher than some
celing effect
refers an effect whereby data
cannot take on a value higher than some
floor effect
How can researcher bias be lessened?
-using designs where the researcher is blind to conditions
-comparisons cross-checked for consistency in recordings
An ________ _________ is a measure of the
“influence” of a journal
• Measures the ___________ with which the
"average article" in a journal has been cited in
a given period of time
• Journal Impact Factors are produced by
• Impact factor available thru (1) _______________ ____________
(2) on a journal’s _________ _________
impact factors
Thomson Institute for Scientific Information
University Libraries; journal's website
Journals which publish on more specialized
topics will have _______ impact factors than
those which publish on more general topics
Other factors influencing impact factors?
Date of publication
– Size of journal
– Average number of citations
– Number of review articles
– Type of field
We’ve now learned about ________ of evidence
and ___________ of evidence in terms of:
– Study design (experiment, quasi‐experiment, etc.)
– Validity (internal, external, construct, etc.)
• The highest quality, strongest and/or most
innovative articles will often be the most
highly influential
– Journal impact factors!
quality; strength
What section of a research paper summarizes data and statistical analysis? It uses _____________ statistics and includes tables and figures.
results section
_____________ statistics summarize, simplify,
and describe measurements
– Measures of “_______ __________: mean, median,
– Measures of ___________: range, variance,
standard deviation
central tendency
____________ statistics help researchers
interpret the data

What are some examples?
T‐tests, ANOVA, ANCOVA, Wilcoxon sign‐rank
test, Tukey’s HSD, etc.
The appropriateness of the descriptive and
inferential statistics for data affect _____ _________ __________
statistical conclusion validity
What are the different scales of measurement?
Nominal Scale
• Ordinal Scale
• Interval Scale
• Ratio Scale
Naming scale
– Each number reflects a category

What are some examples?

We can only look at _____________, can't ____ or __________

men/women, type of hearing loss
(conductive, sensorineural, mixed); desire to upgrade
to AuD (yes/no); code as 1, 2, 3, etc.; phoneme
production (correct/incorrect); diagnostic category

frequencies; add/subtract
Scale indicating rank order
– Reflects the order, but not the amount

What are some examples?

We can calculate the _________ rankin but not much more.

ranked severity groups,
socioeconomic status (low‐, middle‐, upper
class), rank in class, stimulus complexity
(easy, moderate, difficult)

can only be represented
by integers (whole numbers like 1, 2, 3…)
– Nominal and ordinal data

theoretically capable
of taking on fractional units of measurement –
decimals (sometimes rounded)
– Interval and ratio data
discrete variables

continuous variables
Scale with equal intervals
–The scale indicates amount, but
with no zero point

What are some examples?

We can ....
interval scales

temperature on the
Celsius scale, most assessments

Can add subtract, but typically
not multiply or divide
Scale that fits the number system well
– Includes equal intervals and a true zero ‐ “zero
means zero” ; "score" data


We can...
ratio scale

Ratio Scales
• Scale that fits the number system well
– Includes equal intervals and a true zero ‐ “zero
means zero”
• Examples: time, distance, frequency, weight,
volume, etc., vowel duration, sound frequency,
air pressure, number of misarticulations,
diadochokinetic rate, speech intelligibility score

Perform any mathematical equation
__________: Experiments, comparative studies
____________: Correlational studies, survey
research, retrospective research
_______: Observational research, case studies,
Interview research*
________: Interview research*, narrative
research, testimonials
*Strength is higher if structured interviews are used
2‐D graphs have:
– An_________ (abscissa)
– A ________ (ordinate)
Frequency or grouped frequency can be
represented as either:
___________ Bar graph showing a count on the y‐axis
– _______ __________: Line graph showing a count on the yaxis
frequency polygon
shows the %
or proportion of scores that fall within each
range of values
– Similar to histogram, but y‐axis is different
relative frequency distribution
whole pie is 100%; pieces of pie
represent fractions of 100% for each category
pie chart
Some distributions are ______________ (right side is the
mirror image of the left side)
– E.g., ________ distributions: “bell curve”
• Other distributions are not symmetric
– ___________ _________: “Tail” tends toward positive direction
– ___________ ____________: “Tail” tends toward negative direction
positively skewed
negatively skewed
We may want to know where “most of the
participants fall” on the distribution
– This is called the _________ ___________ of the
– Measures of central tendency include __________ , ____________, ___________
central tendency

mean median mode
Central tendency = _______ of a distribution
• Measures of central tendency:
– _______ (average)
– ___________ (middle score in rank‐ordered list)
– _______ (most frequent score)
___________ – one most frequency score
__________ – two most frequency scores
We can quantify __________(or horizontal spread)
of a distribution by using.... (2)
____________ = (standard deviation)2
(square of standard deviation)
___________ _____________ = (variance)
(square root of the variance)
variance & standard deviation
standard deviation
A common type of unimodal distribution is the
____________ distribution
To calculate the variance, follow these steps:
– Work out the mean (average of the numbers)
– Then for each number: subtract the mean and
square the result (the squared difference)
– Then work out the average of those squared
This gives you the variance!
– Standard deviation is the square root of the
In a histogram, counts go on the ____ axis.
__________ statistics summarize, simplify,
and describe measurements. They include measures of ____________ __________ (mean, median, and mode; and measures of _______________: range, variance, SD.
descriptive statistics
central tendency
____________ statistics help researchers
interpret the data. These include: T‐tests, ANOVA, ANCOVA, Wilcoxon sign‐rank
test, Tukey’s HSD, etc.
inferential statistics
_________ _________ take into account (a) group mean differences relative to (b) ____________ and (c)
test statistics
number of participants
_____________ ______________ statistics provides a standard way of telling whether differences in means across levels of the IV(s) outweigh variability in each level relative to number of participants
• If the inferential test statistic passes a
specified __________, then there is a significant effect of that variable; otherwise there is not a significant effect.
inferential statistics
If there is statistical __________, then there’s no
significant effect of the IV(s)
If there is statistical __________, then there is a
statistically significant effect of the IV(s)
What are examples of some test statistics?
t scores (t-tests), z scores (z-tests), F (for ANOVA)
“Cutoff value” specifies the boundary between an extreme score from a non‐extreme score.
If a test statistic is in the “_________ __________ region”, then
we conclude the IV had a statistically significant effect
extreme score region
What are the locations of the critical region boundaries for three different levels of significance? .
α = .05,
α = .01, and α = .001
Descriptive statistics for a sample are referred to as _________ ___________.
– Mean (M), standard dev (s), variance (s2)
sample statistics
_________ ___________are abstract or “ideal” values of sample statistics
– Mean (μ), standard dev (σ), variance (σ2)
population parameters
What is the first step in the logic of inferential stats tests? What are the 2 possibilities? These are stated in terms of ___________ _______________ like μ, σ.
Identify & state each hypothesis.

The levels of the IV are equal
The levels of the IV are not equal

population parameters
What is step 2 in the logic of inferential stats tests?
Set the criteria for a decision:

2 substeps:
- determine the statistical test
- determine the cutoff value for the distribution that separates normal from extreme scores
___________ _______________ refers to how subjects are chosen to be part of a study. It refers to drawing a sample from the population in a manner that ensures that each member of the population has an equal change of being chosen for the sample.
random sampling
________________ ____________ is a requirement of a true experiment in which an experimental group and a control group are formed by the experimenter. It is achieved when each subject is just as likely to be assigned to the control group as the experimental group.
random assignment
Research that focuses primarily on theory testing is often called _________ research. _____________ research seeks to go from data directly to a real-world application.
What is the college sophomore problem?
The worry that, because college sophomores are the subjects in an extremely large number of psychological investigations, the generality of the results is in question.
What is the idea that a new theory in science must make contact with previously established empirical facts? To be considered an advance, it must not only explain new facts, but also account for old ones.
principle of connectivity
The principle of __________________________ involves scientists and those who apply scientific knowledge making a judgement about where the preponderance of evidence points. It is a useful tool for the lay consumer of scientific information and particularly useful in evaluating psychological claims. It urges us to base conclusions on data that arise from a number of slightly different experimental sources.
converging evidence
A design known as the _____________ has been used to investigate the televised-violence/aggressive behavior issue.
field experiment
The ______________________________ refers to the failure of some people to respond with help when observing another individual in an emergency situation.
unresponsive bystander phenomenom
To conclude that there is a significant causal relationship between variable A and behavior B does not mean that variable A...
is the ONLY cause of behavior B
A factor that influences behavior may have different effects when operating in conjunction with another factor compared to when it is acting alone. This is called the concept of _____________. The magnitude of one variable may depend on the level of another.
____________________ means that it is more likely than not, but does not hold true in all cases.
probabilistic trend
The prediction of outcomes based on group characteristics is called ______________________.
aggregate/actuarial prediciton
_____________________ is the tendency for people to see links between events in the past and events in the future when the two are really independent.
gambler's fallacy
What is important when dealing with multiple causation?
For IV #1... (A,B)

What does H0 say? What is the equation that illustrates this?
What does H1 say? What is the equation that illustrates this?
“The levels of the IV are statistically equal
- There is no difference between the levels”
H0: uA = uB
"The levels of the IV are statistically
nonequal - There is a difference between the
H1: uA ≠ uB
What is step 3 in the logic of inferential stats tests?
compute test statistics from the actual data
What is step 4 in the logic of inferential stats tests?
make a statistical decision and interpret the results relative to the research question.
What are the potential benefits of studying more than one IV in a single study?
-possibility of looking for interactions among different variables
An unexpected pattern of data
in which one or more condition(s) do not
follow the trends seen for the individual IV’s
in the rest of the study
A study that concludes that there are very different outcomes for men and women under different drug dosages revealed the ____________ of IV of gender and IV of drug dosage. Thus, the ________ of drug dosage depends on whether the participant is male or female.
Interactions become clear when studying two IVs simultaneously. This is done using a ____________ study, or one that has more than 1 IV.
________________ is a study where there is more than one IV and there are participants in all possible pairings of levels of the IV’s. These are the norm in studies with more than 1 IV.
First, determine how many ______ there are. This will tell you how many possible ___________________ and _______________ there are. For each, there will be a separate ________________.
main effects
test statistic
A single IV will have...

Two IV’s have...
one pair of hypotheses for each DV

3 pairs of hypotheses for each DV
(one relating to possible main effect of IV 1, one for main effect of IV 2, one for interaction of IV 1 and 2
In an experient w/ one IV ; three levels (multivalent study - experiment or quasiexperiment):
Level A, Level B, Level C
– H0: ““The levels of the IV are statistically equal
- There is no difference among the groups”
H0: uA = uB = uC
– H1: “The levels of the IV are statistically
nonequal - There is a diff. among the groups”
H1: uA ≠ uB and/or uB ≠ uC and/or uA ≠ uC (*post-hoc test needed)
1. One IV with two levels (bivalent
study - experiment or quasi-experiment):
Level A and Level B
– H0: “The levels of the IV are statistically equal -
There is no difference between the levels”
H0: uA = uB
– H1: “The levels of the IV are statistically
nonequal - There is a diff. between the groups”
H1: uA ≠ uB
Interaction between IV #1 and IV #2:
– H0: “IV #1 affects all levels of IV #2 in a
statistically equal manner”
– H1: “IV #1 affects one or more levels IV #2 in a statistically unequal manner”
– No equations required
Cutoff values depend on ________________________ given by:
– Number of ____________ AND/OR
– Number of ________________
degrees of freedom

levels of the IV
This type of statistical test is based on the assumption that data fit a particular shape or distribution (e.g., ‘Gaussian distribution’). What are some examples?

_____________ tests are not based on this assumption.
– Examples: Chi-squared test, Wilcoxon test, Mann-Whitney test, Kruskal-Wallis test

t-test, ANOVA (f)

If you have one IV with two levels, you use a ...

If you have one IV with three or more levels, you use a(n)...

If you have two or more IVs, you use...
t-test (or ANOVA)


What is the "extreme" region of a distribution?

Example: With df = 20, the critical t value is +/-2.09.
If we get t(20) = 5.73, it’s significant! (p < .0001)
5% or smaller portion of the curve
What are the (3) types of causation?

_______________: Where a variable is necessary and sufficient to produce an effect on a DV

_________________: A causal variable might be necessary for an effect on the DV, but the effect depends on another variable.

______________: A causal variable might be neither necessary nor sufficient, but its presence increases the statistical probability of an effect.
strongest form

weaker form

weak form
Any variable that confounds the ability of the chosen sample to represent the population parameter from which it was drawn (bias in representation due to selection, affects external & internal validity __________________________
selection bias
How is selection bias minimized?
-Using random assignment to the levels of IV
-Also by matching participants in terms of groups
-Developing well-defined inclusion criteria
-Develop exclusion criteria to eliminate unwanted participants that might bias a sample
-Sampling as close to randomly as possible
Defined as validity of the inference about
whether the causal relationship holds over
people, settings, treatment variables,
measurement variables, and time ________________________
external validity
What are the (4) types of external validity?
population validity
treatment variation validity
temporal validity
ecological validity
__________ describes an all‐inclusive data set about which researchers want to draw a conclusion.
A _________ is just a subset of the population.
There will inevitably be some amount of
______________, i.e., difference between the measures collected for a sample and the population it’s believed to represent
sampling error
This refers to the ability to generalize from the sample in a study to a larger population. The _____________ population is the larger population to whom the results are generalized. The ____________________________ population is the one that is available to the researcher.

target population

experimentally accessible population
How can generalization be achieved easily?
If the researcher uses random selection
This involves drawing observations from a population so that each individual has an equal chance of being selected _________________. This is different than __________________, which sets out to create equivalent groups by balancing them based on specific characteristics.
random sampling
random assignment
____________________ is a sampling method where each individual has an equal probability of being selected, "true random selection."
simple random sampling
___________________ involves dividing a population into subgroups called strata to assure that certain segments of the population are adequately represented in a sample. ______________ means a subdivision/group.
stratified sampling

________________________ refers to the extent to which results of the experiment can be generalized across time.
temporal validity
____________________ refers to the generalizability of results across variations in treatment. It's an issue because the administration of the treatment can vary from one administration to the next.
treatment variation validity/transferability
______________________ refers to the degree to which behaviors that are observed in a study reflect the behaviors that occur in natural settings.
ecological validity
Refers to the extent that causal inferences are justified based on observed changes in a DV in response to systematic variations in an IV

The strength of depends on to
what extent extraneous variables have been removed from the study.
internal validity
An most important possible threat to internal
validity is not having a high enough constraint
study design

How do we minimize this?
study design threat

random assignment
manipulation to remove extraneous variables
The fact that an individual changes/matures over time

What is the problem with this?

There is no control group to compare for effects of natural maturation
Effects of previous testing on performance

What can we do to guard against this?
testing effects

use diff questions/assessment
wait a long time before reassessing
A change in a DV due to a tx effect that is not immediately observable but tends to become increasingly observable over a span of time

To guard against this...?
sleeper effect

plan appropriate treatment interval and track participants after study has ended
This is any event between the beginning of a treatment and the measurement of the DV that could produce the outcome

How can we minimize this?

make sure no new events occur after beginning of tx
Refers to the fact that some individuals 'drop out' before completing a study

Ways to minimize?

give incentives for participating, enroll new participants in the study