Test #1 Flashcards
(134 cards)
1
Q
What do quantitative methods rely on?
A
The identification of variables
2
Q
What is the unit of analysis in quantitative research?
A
Quantity
3
Q
What types of data gathering methods are used for quantitative studies?
A
Surveys and questionnaires
4
Q
What is the logic flow in quantitative analysis?
A
From the generalized (theory) to the specific (research conclusion)
5
Q
What are validity and reliability related to?
A
The method
6
Q
How truthful the data with be.
A
Validity
7
Q
How consistent the data will be.
A
Reliability
8
Q
The thing you want to study.
A
Concept
9
Q
What can a concept be?
A
An object, event, relationship, or process.
10
Q
A set of connected concepts form what?
A
A conceptual scheme.
11
Q
What does a conceptual scheme do?
A
Specifies and clarifies the relationship amount them.
12
Q
Only when can concepts become constructs?
A
When they are linked to other concepts.
13
Q
Identify the theoretical construct as it is presented in research questions and hypothesis.
A
Variables
14
Q
Denotes how the variable is observed and measured.
A
Operationalization
15
Q
An educated presumption based on a scholar’s review of the research literature.
A
Hypothesis
16
Q
Describes the logical explanation of the difference or relationship between to or more variables.
A
What a hypothesis describes.
17
Q
What does a hypothesis state?
A
The nature of the relationship between variables
18
Q
A precise statement indicating the nature and direction of the relationship or difference between variables.
A
Directional hypothesis
19
Q
States that a difference will occur but does not state the direction of that difference.
A
No directional hypothesis.
20
Q
The implicit complementary statement to the research hypothesis.
A
Null hypothesis
21
Q
What does a null hypothesis state?
A
No difference or no relationship except for one due to chance exists between the variables.
22
Q
What must a variable have?
A
Two or more levels. (Male and female)
23
Q
When can something be identified as a variable?
A
When it fluctuates in the research study. (Sex cannot be a variable if only women are studied.)
24
Q
What must variables be identified as?
A
Independent or dependent
25
Manipulated by the researcher or the variable that alters the dependent variable.
Independent variable
26
Influences or change by the independent variable.
Dependent variable
27
When reliability is achieved....
Data are free from systematic errors.
28
What must the hypothesis be?
Testable
29
Null hypothesis are assumed to be true until what?
Support for the research hypothesis is demonstrated.
30
What do qualitative studies use for data?
Discourse. Focuses on empirical , interpretive, and inductive approaches.
31
Naturally occurring talk or gestures captured in a variety of forms and remains as it occurs.
Discourse
32
Everything influences everything else.
Mutual simultaneous shaping
33
What is mutual simultaneous shaping useful for?
Studying sensitive topics
34
The reasoning used by qualitative researchers to discover and develop theories as they emerge from the data.
Inductive analysis
35
Moving from the specific to the general.
Inductive reasoning
36
The extent to which interpretations can be validated as true, correct, and dependable.
Credibility
37
The use of several kinds of methods or data to bring credibility to their findings.
Triangulation
38
Using a variety of data sources in one study.
Data triangulation
39
Several researchers participate in the research.
Investigator triangulation
40
Researchers from a variety of disciplines work together on a research project.
Interdisciplinary triangulation
41
The prices of taking the research findings back to individuals from whom data were collected or observed.
Member validation
42
How are research questions stated for qualitative research?
Broadly and generally non directional
43
The researcher develops an interpretation based on his/her subjective position.
Researcher construction
44
Relies on a mix of objective and subjective elements. Acknowledges that there are tangible artifacts or objective sources of meaning.
Subjective valuing
45
Relies on tangible artifacts which are believed to be accurate representations of the phenomenon.
Contingent Accuracy
46
What are the 3 ways to interpret meaning in qualitative research?
Researcher construction
Subjective valuing
Contingent accuracy
47
Which is the most objective of the three ways to interpret qualitative research?
Contingent accuracy
48
Evidence can be identified and stand on its own.
Micro level evidence
49
Broad-scale evidence and mid level data are somewhere in between.
Macro level evidence
50
When does selection bias occur?
When data stand out to a researcher.
51
The influence of the researcher on the interaction among participants
Reactivity bias
52
What does quantitative research rely on?
Formal logic
53
What does qualitative research rely on?
Interpretation
54
How do quantitative studies select participants?
Randomly
55
How do qualitative studies select participants?
Purposefully
56
Consistency in procedures and reactions of participants
Reliability
57
Compiled detailed record or log of your research process and have a third party conduct the same research according to your log.
Audit trial
58
What are a researcher’a credibility defense?
Triangulation
Member validation
Audit trials
59
What are researchers 2 ethical responsibilities?
Scientific and ethical (protecting research participants)
60
The guidelines adopted by federal departments and agencies regarding research ethics.
The Belmont report
61
What does the Belmont report contain?
Beneficence, respect for persons, justice
62
Protection of the participants well being.
Beneficence
63
Treat individuals as capable of making decisions.
Respect for Persons (the Belmont report)
64
Matter of fairness
Justice (the Belmont report)
65
What does the Belmont report apply to?
Academic research, not private companies
66
What are numbers used as a tool for?
Identifying and presenting information.
67
What do numbers link?
The conceptual to the empirical
68
What connects numbers to something?
Measurement
69
What are the four levels of measurement? (In order)
1. Nominal (lowest)
2. Ordinal
3. Interval
4. Ratio
70
The presence or absence of a certain characteristic. (Yes/no questions) (one or the other)
Nominal
71
What is the only meaningful central tendency for nominal data?
Mode
72
What are the central tendencies?
Mean, median, mode
73
Categorical numbers that also represent rank order. (Please rank your favorite type of food from 5 to 1)
Ordinal
74
When does mathematical zero does not exist?
Ordinal data
75
Do the intervals between data indicate absolute or identical difference in ordinal data?
No
76
What is/are the meaningful central tendencies in ordinal data?
Mode and median
77
What must data options be on surveys?
Mutually exclusive and exhaustive
78
Contains all properties or ordinal scales and the numbers can be mathematically interpreted (real numbers).
Interval
79
What does interval data identify?
The exact difference between and among scores. (Categories are assumed to be separated by equal distances)
80
What does mathematical zero mean in interval data?
It is acknowledged but no mathematical meaning. (Ex. 0 degrees does not mean no temp.)
81
What is measured in interval data?
Psychological responses. (Opinions/emotion)
82
What central tendencies can be used in interval data?
Mean, median, and mode.
83
Contains all the properties of interval scales and zero is absolute, mathematically meaningful.
Ratio data
84
What are the numbers in ratio data?
Mathematically accurate
85
What is the most powerful data that naturally enables the use of all the meaningful statistical process for data analysis?
Ratio data
86
What does the best type of data measurement depend on?
The research question
87
Is the measurement scale measuring what it is supposed to measure?
Measurement validity
88
Degree of internal consistency among similar items.
Internal reliability
89
Indicates consistency over time. Use of the same scale two different times to the same respondents.
Test-retest reliability
90
Indicates consistency over time. Splits the scale items in half and uses the first half first and the second half later to retest.
Split-half reliability
91
All units (people or things) possessing the attributes and characteristics of interest.
Population
92
Study of the entire target population
Census
93
Subset of a population
Sample
94
Extent to which conclusions developed from data collected from sample can be extended to its population.
Generalizability
95
What do representative samples minimize?
Sampling errors and selection bias
96
What is the only way representativeness can be assured?
Random sampling
97
What do good samples have?
High generalizability
98
When will the sampling error occur?
In every study using samples.
99
Difference between statistic value from sampling procedure and true population parameter value.
Sampling error
100
When can the sampling be almost as accurate as census?
When sampling errors are under control.
101
Random sampling =?
Probability
102
The probability to be selective as a part of sample group is known in?
Advance and equal
103
When probability for selection is equal and known in advance, the selection becomes what?
Random
104
Every possible sample within a population has equal and known chance of being selected.
Ex. Drawing a name out of a hat
Simple random sampling
105
Random sample within predetermined subcategories.
| Ex. If target population consists of 57% female and 43% male, then select samples of the female and male portions.
Stratified random sampling
106
Each sampling strata is proportional to the actual population.
Proportional in stratified random sampling
107
Each sampling strata is disproportional to the population and is based on the researcher’s purpose.
Ex. Randomly select 50% of tv watching and 50% of non-TV watching households as sampling strata to study the diff between them
Disproportional in stratified random sampling
108
Multiple groups
Strata
109
Clusters of population units are selected at random and all of randomly selected units in that cluster are selected as samples.
Cluster sampling
110
When is cluster sampling useful?
When adequate sampling from which you can obtain the list of your samples are readily available.
111
With the given sample size needed, figure out sampling interval (k) from a sample frame and randomly select starting point within the interval range, and select every kth number of samples for that point.
Ex. From a pop or 1000 ppl, you need 100 ppl. This k=10 (1000/10) =10
Systematic sampling
112
What must you have to use systematic sampling?
An appropriate sampling list.
113
It is a non random procedure in which the probability of being selected is not known beforehand.
Non probability sampling
114
Relatively low sample representativeness that are selected based on a researcher’s convenience. Room for bias and sample error
Convenient sampling
115
Researcher exerts an effort in selecting samples with specific purpose
Purposive sampling
116
Predetermined quota of units is used to select samples from population segments based on researcher’s need (control characteristics).
Quota sampling
117
When is quota sampling commonly used?
In personal interviews
118
Number of people/units from whom you need to collect data.
Sample size.
119
When is sample size determined
Prior to selecting the sample
120
What can a large sample size decrease?
Sampling error
121
What sampling size is the worst?
Small and non random
122
States the expected relationship or difference between two or more variables.
Research hypothesis
123
What is sufficient evidence obtained from?
The significance level
124
What value is used as the significance level?
P value
125
Probability of obtaining a certain result as a result of a sampling error.
P value
126
Act of decision making based on the significance level.
Hypothesis testing
127
The lower the p value gets, the better
Probability of having a solid result
128
When is the predetermined significance level set?
For each statistical test before beginning research
129
What does the predetermined p value indicate?
The level of error the researcher is willing to accept as statistically meaningful finding
130
What level of p is generally accepted in social sciences?
.05 or lower
131
When p is higher than .05, it means...
The evidence supporting the research hypothesis is not strong enough and not statistically significant. Null hypothesis stays
132
When null hypothesis is rejected and the null is true. (Saying there’s something going on when, in fact, there isn’t. Set the acceptable p value too high)
Type 1 error
133
When null hypothesis is not rejected when the null is false. (Saying there’s nothing going on when there is. P value is too low and too strict standards)
Type two error
134
Why can p value by itself be misleading?
Because of sample size
