Research Flashcards
1
Q
What is research?
A
The systemic process of collecting and analyzing data
2
Q
What is evidence based inquiry?
A
Search for knowledge using empirical data which has been gathered systematically.
3
Q
What is inductive research?
A
Begins at the real world, practical level. Descriptive, correlational, or historical and leads to the building of theory.
4
Q
What is deductive research?
A
- Springs from theory that is already established.
- Tries to determine what the relationships are between elements of the theory
- May be experimental in nature
5
Q
Survey
A
- Non experimental
- Measures attitudes and perceptions
- Not easily generalizable unless subject pool is representative
6
Q
Descriptive research
A
- Non experimental
- Describes an existing state of events
7
Q
Comparative research
A
- Non experimental
- Investigates if there are differences between one or more groups
- No manipulation of conditions
8
Q
Correlational research
A
- Non-experimental
- Uses the correlation coefficient to determine the degree of relationship between two or more variables or phenomena.
9
Q
Ex post facto research
A
- Non- experimental
- This research design studies possible causal relationships among variables ex post facto (after the fact).
- No manipulation of variables
- Generate several reasons (causes) for the relationship
- Statistics used are t-test and analysis of variance
10
Q
True experiment
A
- Experimental and control groups with random assignment
- Determine cause-and-effect relationships
11
Q
3 types of experiments
A
- Treatment and control group with post test only
- Treatment and control group with pretest and post test
- Two different treatment groups with control group and post test
12
Q
Quasi experiment
A
- Similar to experimental research except that randomization of subjects to treatment and control groups is not possible.
- Example two classrooms of 4th graders
13
Q
Qualitative research
A
Emphasizes gathering data about naturally occurring phenomena (individuals and groups living experiences) and events.
14
Q
Two types of interactive qualitative research designs
A
- Case study: in depth examination of a particular case
- Ethnography: description and interpretation of cultural or social group or system
15
Q
Non interactive qualitative research design
A
- Analytical research conducted primarily through document analysis.
- Examples: historical analysis, biographical analysis (written or oral), legal analyses (law and court decisions).
16
Q
Mixed method research design
A
- Combine quantitative and qualitative in the same research effort
- Typically used sequentially
17
Q
Single-subject design
A
Studies the effects of a program or treatment on an individual or group treated as an individual usually after a baseline has been established
18
Q
Action research
A
Attempt to improve services or a program. Usually has an evaluative function.
19
Q
Pilot study
A
A small scale research effort often used to detriment the feasibility of large scale effort.
20
Q
Longitudinal research
A
Collecting data from the same forks of individuals over a period of time also called a panel study.
21
Q
Cross sectional research
A
Collecting data from different groups at the same time and examining the differences.
22
Q
Examining what changes occur within the members of a group
A
Within-subjects
23
Q
Examining what changes occur between two or more groups
A
Between subjects
24
Q
Meta-analysis
A
Research comparing findings across studies
25
Internal validity
Extraneous variables have been controlled
26
Confounding variables to internal validity
1. Selection of subjects (not randomly selected
2. Instrumentation
3. Maturation (changes do to maturation not treatment)
4. Mortality or attrition (losing subjects )
5. Experimenter bias
6. History or extraneous incidents
7. Statistical regression (subjects are recruited because of extreme high or low scores
27
External validity
Results are generalizable
28
Threats to external validity
1. Selection of subjects
2. Ecological validity (generalizable form one setting or circumstance to another)
3. Reactivity
4. Novelty and disruption (being selected energizing or exciting swaying response)
29
4 types of reactivity
1. Hawthorne effect - subject knows they are being watched
2. Demand characteristics- what subject has been told or knowledge they have acquired influencing performance
3. Experimenter bias, rosenthal, pygmalion
4. Placebo
30
4 Levels of measurement
1. Nominal
2. Ordinal
3. Interval
4. Ratio
31
Nominal measurement
1. Numbers represent qualities or categories (male and female)
2. Use a non parametric statistic such as chi-square
32
Ordinal measurement
1. Represents differences in magnitudes of the variable
2.data that can be ranked
33
Interval measurement
1. The intervals between the numbers on a scale contain the same amount of the variable.
2. Example: on a Standardized test the distance (interval) between 11 and 12 is the same as the distance between 24 and 25.
3. Example Fahrenheit
34
Ratio measurement
1. Numbers are on a scale which has a true zero.
2. Numbers can be compared by ratios
3. You cannot say someone is twice as introverted as someone else because there is no base
4. Weight has a true zero for example because you cannot be negative pounds
35
Sampling
Selection of a part of the population
36
Random sampling
Equal and independent chance of being selected
37
Stratified sampling
Major subgroups in the population will be sampled (ethnicity, gender, race)
38
Proportional stratified sampling
Randomly selecting the same proportion of individuals in subgroups which is representative of population.
Example: one half of population is Hispanic one half is white sample would mirror these proportions
39
Cluster sampling
Naturally occurring groups of individuals such as classrooms or City blocks. Clusters randomly selected.
40
Sample size
Size influences statistical hypothesis testing.
Suggested minimum sample sizes
Correlational: 30
Ex post facto and experiment: 15
Survey: 100
41
4 types of statistic analysis
1. Descriptive - describe data collected (summary)
2. Inferential - make inferences from sample to population
3. Parametric - data normally distributed
4. Non parametric - cannot be normally distributed (chi squared)
42
Independent variable
Variable you manipulate
43
Dependent variable
Variable you are measuring or trying to change. Depends upon the value of the independent variable.
44
Null hypothesis
No difference between the variables or groups measured
45
Alternative hypothesis (directional)
One groups scores will be significantly different (one tailed test)
46
Alternative hypothesis (nondirectional)
There will be differences between the groups but which group had higher or lower scores is not indicated (two-tailed test)
47
Significance level
Significant level you select will determine the likelihood or making an error in accepting or rejecting the null
48
Type I or Alpha error
Rejection of null when it is correct
False positive
49
Type II error (beta)
Failure to reject the null hypothesis when there is in fact a difference
False negative
50
As significance level goes down ( .05 to .01) type 1 error decreases and type two error increases
Alpha (Type I) error: Reject (null hypothesis) when shouldn’t.
Beta (Type II) error: Retain (null hypothesis) when shouldn’t.
51
T-test
Used to determine whether the mean scores of TWO groups are significantly different from each other.
52
One-way Analysis of Variance
One variable and different levels (therapists at LPC, LSW, PHD) uses F values and F distribution.
53
Factorial analysis of variance (ANOVA)
Factorial (ANOVA): simultaneously determine whether mean scores in two or more variables (factors) differ significantly.
1 dependent variable (self esteem)
2 or more independent variables (gender and therapist level)
54
Multivariate analysis of variance (MANOVA)
More than one dependent variable
You must use MANOVA instead of ANOVA
55
Analysis of Covariance (ANCOVA)
Similar to analysis of variance except that the Influence of one or more independent variables on the dependent variable is controlled.
56
What test do you apply if an ANOVA test yields a significant F value to determine whether a particular group mean or combination of group means are significantly different?
Post hot or multiple comparison tests
57
Scheffe’s, Tukey’s HSD, Newman-Keuls, Duncan’s new multiple range test are all examples of what kind of tests?
Post hoc and multiple comparison tests
58
When do you use a non parametric test?
If a distribution of scores is not normally distributed or the variance of your sample is similar to the variance of the population (homogeneity).
59
Mann-Whitney U test
Nonparametric test
When you collect data from two samples that are independent from each other and the scores are not normally distributed.
60
Wilcoxen signed-rank test
Scores from two samples and these scores are correlated but they do not approximate a normal distribution.
61
Kruskal-Wallis test
Non parametric test
When you have more than two mean scores on a single variable. This is a nonparametric one-way analysis of variance.
62
Chi squared
Nonparametric test
Used when you have nominal data (groups or categories)
Used to determine whether two distributions differ significantly
63
Solomon four-group design
Examines the effect of any pretest used on the experimental treatment.
64
Multiple regression
Use of the correlation coefficient to determine the strength of the relationship of predictor (independent) variable on a criterion (dependent variable.
Adds together the predictive powe of several independent predictors (independent variables)
examples of predictors variables GPA, class rank, ACT
65
Scatterplot
Graphic representations of the relationship between two variables for a group of individuals.
Reference photo
66
Factor analysis
Use of correlation coefficient to determine whether a set of variables can be reduced to a smaller number of factors.
Example: a factor analysis of a long inventory with 15 scales may uncover only 4 or 5 factors that are independent of one another because parts of the scales overlap
67
Likert scale
Measures attitudes and opinions
(Agree, strong agree, disagree, strongly agree)
68
Cross- sectional study
Studying or measuring characteristics of several groups at the same time
69
Longitudinal study
Studying or measuring characteristics of a group over time
70
Double blind
When neither researcher nor the subject knows who is receiving the active substance or the placebo
71
Halo effect
Tendency for the observer to form an early impression of the person being observed and that creating a bias.
Can be positive or negative
72
Formative evaluation
Determine how well a new technique, process or, treatment works.
“Process evaluation”
73
Summative evaluation
Summary or product evaluation used to measure how well an agency or program has met their goals.
“Product evaluation”
