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96 Cards in this Set

  • Front
  • Back
True Results
- results that would be obtained by conducting a census of the entire population
- they are TRUE in the sense that they are free of sampling errors
Chi-Square
- usual test of null hypothesis for differences between frequencies (number of cases or n)
- symbol is x2
- not a descriptive statistics
Degrees of Freedom (df)
- calculates to see of null hypothesis is correct
- not a descriptive statistic
- thought of as sub steps in mathematical procedure for obtaining the value of p

Example: x2 = 4.00, df = 1, P< 0.05
P (Probability)
- when probability of null hypothesis is correct is .05 or less
- differences is STATISTICALLY SIGNIFICANT at the 0.05 level
What happens if p is above 0.05?
Cannot reject null hypothesis & report it as statistically insignificant result
Univariate Analysis
- chi-square in which each participant is classified in only 1 way (ex. which candidate do they prefer)
When researchers study a sample, are the results called "true results" or "observed results"?
Observed results
Should the typical consumer try to interpret the value of df?
No
If a researcher fails to reject a null hypothesis, is the difference in question statistically significant?
No because the P value will be greater than 0.05
Bivariate Analysis
Analysis in which each participant is classified in terms of 2 variables in a chi-square test
Null Hypothesis
- No true difference
- if all members of the population had been studied, the research would've found no difference among the 3 methods

5 out of 100 times the null hypothesis is right
Type I Error
When null hypothesis is true and it was rejected
Type II Error
null hypothesis should have been rejected but the significance test failed to lead the researchers to the correct decision
Frequency Distribution
- Describe quantitative data
- can construct a figure called a frequency polygon to show data
Skewed
Have a tail on 1 side & not the other
Positive Skew
Skewed to the right

ex. Income
Negative Skew
Skewed to the left

Ex. test basic math skills
Mean
- most frequently used average
- balance point in a distribution
- value around which the deviations sum to zero
What is M a symbol of?
Mean of a population
What is m a symbol of?
Mean of a sample
What symbol do statisticians use?
x̄, pronounced "x bar"
Median
- the middle score
- used to describe the averaged of skewed distributions
Mode
- most frequently occurring score
- seldom reported in formal research reports (b/c there can be more than 1 mode)
Measures of Central Tendency
Synonym for "averages"
Standard Deviation
- one of 2 measurements used to describe variability
- symbol = S or SD for a population, s or sd for a sample
- smaller variability = small standard of deviation
Variability
Amount by which participants differ from each other
How many participants are within 1 standard-deviation unit of the mean if the distribution is normal?
68% of participants
Which average is usually reported when the standard of deviation is reported?
Mean
Range
- highest score minus the lowest score
- based on the 2 most extreme scores
- considered unreliable
Interquartile Range
- range between quarters (range of 2 middle quarters)
- range of the middle 50% of participants
- used to help get around unreliability of using just range
Should the mean or median be used w/ ordinal data?
Median
Large Interquartile Range = __________ (Lower/Higher) Variability
Higher
Pearson Product-Moment Correlation Coefficient
- most widely used coefficient for examining relationships between 2 quantitative sets of scores
- symbol = "r" called the "Pearson r"
Coefficient of Determination
- Pearson r doesn't correlate to percetnages; convert Pearson r to this statistic to get percentages
- ex. if Pearson r = 0.50, you square 0.05 = 0.25 x 100% = 25%
T test
- used to test null hypothesis regarding the observed differences between 2 means
When a researcher uses a large sample, are they "more likely" or "less likely" to reject the null hypothesis than when a researcher uses a small sample?
More likely
What does ANOVA stand for?
Analysis of Variance
If a researcher compares 2 means for significance, will ANOVA & the t test yield the same probability?
Yes
If ANOVA yields p > 0.05, are the differences statistically significant?
No
One-Way ANOVA (Single-Factor ANOVA)
When participants have been classified in only 1 way
If an overall ANOVA for 3 or more means is significant, it can be followed by what test to determine the significance of the differences among the individual pairs of means?
Multiple Comparisons Test
Is it possible for a small difference to be statistically significant?
Yes
What are the types of considerations for determining practical significance?
1) Cost-Benefit Analysis
2) Crucial Difference
3) Client Acceptability
4) Public & Political Acceptability
5) Ethical & Legal Implications
Does a crucial difference need to be numerically large to be of practical significance?
Yes
Should the acceptability of a treatment to the clients be considered when determining practical significance?
Yes
True or False: Ethical considerations should play no role in the interpretation of the results of a study
False
For the results of 2 studies to be comparable, they need to be what?
Standardized (so both differences can be expressed on the same scale)
Effect-Size
- the magnitude (i.e. size) of a difference when it's expressed on standardized scale
What are the universally accepted standards for describing effect size?
There are none
What's the "effective range" of standard deviation units on both sides of the mean?
- effective range from 0.00 (no difference) to 3.00 (maximum difference)
What value of d is associated w/ "extremely large"?
d = 1.40+
When will a negative value of d be obtained?
When the control group's mean is higher than the experimental group's mean
Should a test of statistical significant be conducted before or after computing d?
After
What are 2 measures of effect size that are widely reported?
"d" & "effect size r"
Meta-Analysis
Set of statistical methods for combining the results of previous studies
What 2 types of random errors tend to be canceled out in the process of conducting a meta-analysis?
Random Sampling Errors
Random Errors of Measurement
In a meta-analysis, what is the "main thrust of conclusions" based on?
Mathematical synthesis of statistical results of previous studies
What's the 2nd important characteristics of meta-analysis?
- systematic error from 1 researcher will be moderated by results from studies where those errors weren't made
What is 1 very important way various studies on a given topic differ?
Various researchers use different measures of the same variable
Cohen's d
- ranges from +3.00 to -3.00
- symbol of the measurement of effect size
What should be done when the studies to be used in a meta-analysis have different sample sizes?
- d value should be figured for each study, averaged, & treated the same or weighted differently to take into account the varying number of participants
Is a meta-analysis more objective than a review consisting of narrative discussion?
Yes
Publication Bias
- final potential weakness of meta-analysis
- researcher may choose to not publish studies w/ insignificant results
What's a solution for publication bias?
- researchers should search for studies listed in dissertations, convention papers, government reports, & other non-journal sources
Is purposive sampling widely used by qualitative or quantitative researchers?
Qualitative researchers
Purposive Sampling
- judgmental, selective, or subjective sampling
- type of non-probability sampling technique
- units investigated are based off judgment of researcher
Purposive Criterion Sampling
- purposive sampling when there are a number of criteria to be applied in selection of sample
When should participants from diverse sources be used?
In a qualitative study when the researcher has a broader interest than just a single source
Which type of research has more expensive data collection methods?
Qualitative
When has the data collection process become "saturated"?
- the point where several additional participants fail to respond w/ new info that leads to identification of additional themes
What does an interview protocol consist of?
Written directions for conducting the interview as well as a standard set of predetermined questions to be asked of all participants
Who should a pilot test of interview questions be conducted upon?
A few individuals that won't participate in study
Self-Disclosure
Process through which an interviewer can clear the air & clear the mind
Phenomenological Approach
Examining perceptions to acquire knowledge
How many participants are usually in a focus group?
6-12
What are the names of the individuals who lead focus groups?
Facilitator & Moderators
What's a "clear advantage" of using a focus group?
Reveals the evolution of perceptions in a social context
Nonparticipant Observation
Type of observation in which the researcher observes as an outsider
Ethnography
Field of research on cultural issues
Data Triangulation
- use of multiple sources for obtaining data on a research topic
- 2 or more types of participants are used
Methods Triangulation
When a researcher interviews participants & then observes the behavior of the same participants
Researcher Triangulation
Type of triangulation that reduces the possibility that the results of qualitative research represent only the idiosyncratic views of an individual researcher
In peer review, what's a peer?
Person who provides the review (a.k.a. auditor)
Grounded Theory
- inductive method of analysis that can lead to theories of behavior
- starts w/ open coding
Axial Coding
- 2nd step in grounded theory approach
- transcripts of data sources are reexamined w/ purpose of identifying relationships between categories & themes identified during open coding
Constant Comparison
Technical term for constantly comparing each new element of data w/ all previous elements that have been coded
Consensual Qualitative Research (CQR)
- inductive process
- strives to have a team of researchers arrive at a consensus on the meaning of data collected
What's the first step of CQR?
Code data into domains
What's the second step of CQR?
Writing short summaries of participants' ideas
What's the third step of CQR?
Cross-analysis of core ideas into categories based on similarities
How is an external stability check performed in a CQR?
By examining the data in addition to the interview transcripts
How is internal stability examined in CQR?
By determining the extent to which each category was general, typical, or variant
General Domain
Apply to all of participants
Typical Domain
Apply to half or more of participants
Variant Domain
Apply to less than half but more than 2 of the participants
CQR method requires the use of a(n) _________
Auditor (outside expert