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LMSW Exam > Research and Statistics > Flashcards

Research and Statistics Flashcards

1
Q

What’re the steps of the research process?

A

-Problem Formulation

-Methodology

-Actual Collection of Data

-Analysis of Results

-Dissemination of Results

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2
Q

The Research Process: Problem Formulaiton

A

process used by researchers to develop a precise statement that can be operationalized

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3
Q

Problem Formulation: Questions of Hypotheses for Study

A

development of conceptual frameworks and operational concepts

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4
Q

Study Design: Design Concerns

A

insure that the data collected is the same for all participants depends on the training of interviewers and management and control of data

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5
Q

Study Design: Research Resources

A

subjects, the availability of existing data, and the quality of the professional researchers

funding is an important issue and often determines the compromises that researchers make in designing studies

involvement of human subjects: ethical questions

time available for research

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6
Q

Study Design: Ethical Concerns

A

-Research cannot lead to harming clients

-Denial of an intervention may constitute harm

-Informed consent

-Confidentiality

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7
Q

The Research Process: Methodology

A

includes select measurement techniques to be used, the setting where the research is to be conducted, and the population or group to be studied

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8
Q

The Research Process: Actual Collection of Data

A

data security to insure confidentiality

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9
Q

The Research Process: Analysis of Results

A

were the research questions answered? Were the hypothesis accepted or rejected? Research does not simply test a research hypothesis, but implicates the whole body of logically connected knowledge

analysis of results may include changes in related aspects of social work practice and policy

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10
Q

The Research Process: Dissemination of Restuls

A

the cumulative nature of science requires reporting results, conclusions, and interpretations in writing with a view toward publication in professional, preferably refereed journals directed to peers

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11
Q

Research Terminology: Concepts

A

abstractions created by generalizing from specifics

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12
Q

Research Terminology: Operationalizing a Concept

A

reducing a conceptual variable to a set of directions and actions so that a study can proceed in a systematic and replicable manner

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13
Q

Research Terminology: Hypothesis

A

statement about a relationship between two or more variables that can be tested with an outcome that one may confirm, fail to confirm, or refute

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14
Q

What does a hypothesis do?

A

-Asserts there is a relationship between variables

-Specifics the nature of that relationship in a way that allows testing

-Should include empirical referents

-Avoids value judgments

-Is related to a body of theory

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15
Q

Research Terminology: Null Hypothesis

A

asserts there is no significant relationship between two variables

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16
Q

Research Terminology: Variable

A

a characteristic possessed by everyone in the population in varying amounts or kinds

opposite of a constant which refers to a characteristic which does not vary with different people

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17
Q

Variable: Independent Variable

A

the variable believed to cause some variation in another variable

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18
Q

Variable: Dependent Variable

A

the variable whose variation must be explained

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19
Q

Variable: Intervening and Extraneous Variable

A

a variable which comes between the independent and dependent variables

modifies or confounds the variation dependent variable which was thought to result from the effects of the independent variable

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20
Q

Research Terminology: Theory

A

a set of related hypotheses connected so as to explain some phenomena or that predicts phenomena

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21
Q

Research Design: Exploratory Studies

A

used to explore an area of knowledge where little is known and to gain familiarity with real life settings, problems, or phenomena

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22
Q

What’re exploratory studies used for?

A

-clarify concepts and to develop hypotheses for subsequent research

-while used to explore new areas, they are built on careful assessment of knowledge that already exists

-may include systematic review of related literature, a survey of expert, analysis of case material, and participant observation

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23
Q

Research Design: Descriptive Studies

A

used where there is more knowledge than in exploratory studies

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24
Q

What do description studies do?

A

-concerned with ascertaining facts and carefully designed studies of phenomena

-attempt to develop an accurate qualitative and/or quantitative summary or assessment of the situation or phenomena

-they involve studies of a small representative sample so that interferences can be made about the broader population from which the sample is drawn

-describe characteristics of the population or the relationship among given variables

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25
Q

Research Design: Experimental Studies

A

the most rigorous of all studies

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26
Q

Research Design: Experimental Studies

A

-involves testing a prediction by manipulating and independent variable and measuring the effect on a dependent variable

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27
Q

Relationship between the independent and dependent variables?

A

-done under controlled conditions

-research methodology is designed to eliminate the effect of other extraneous variables, thus eliminating alternative explanations for any relationship that is observed

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28
Q

How do you determine causality?

A

-Concomitant Variation

-Time Factor

-Alternating Opening Variables

-Threats to Internal and External Validity

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29
Q

Experimental Studies: Concomitant Variation

A

manipulation of the independent variable is associated with changes in the dependent variable

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30
Q

Experimental Studies: Time Factor

A

the independent variable occurs before change in the dependent variable

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31
Q

Experimental Studies: Alternate Operating Variables

A

refer to observed changes caused by extraneous or unknown variables rather than the hypothesized independent variable since these may

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32
Q

Experimental: Threats to Internal and External Validity

A

alternate operating variables which may influence the results of a study in unknown ways

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33
Q

Threats to Internal and External Validity: History

A

Maturation: effects which are systematic with the passage of time

other changes resulting from the passage of time that may be more powerful than the intervention

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34
Q

Threats to Internal and External Validity: Measurement Decay

A

fatigue of judges or observers

bias in the selection process

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35
Q

Threats to Internal and External Validity: Mortality

A

the loss of some subjects from a sample

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36
Q

Threats to Internal and External Validity: Hawthorne or Test-Taking Effect

A

the act of being studied may in itself produce some change in the subjects

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37
Q

Threats to Internal and External Validity: Placebo

A

treatment given to a control group to convince them they are being exposed to the experimental variable, but exposure is only to a neutral stimulus

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38
Q

Types of Experimental Studies and Design: Field Experiment

A

conducted in a concrete, natural environment

tests a hypothesis but does not have tight control over subjects’ exposure to the experimental variable

39
Q

Types of Experimental Studies and Design: Laboratory Experiments

A

the tests are conducted under tightly controlled laboratory conditions

40
Q

Types of Experimental Studies and Design: Classical Before-After Experimental and Control Group Design with Randomization

A

randomly assign all subjects to experimental and control groups so the researcher is able to assume the two groups are comparable at the start of the study

41
Q

Types of Experimental Studies and Design: Ex-Post Facto Analysis

A

use of statistical analysis of the data to control for the effect of a given variable

42
Q

Measurement Problems: Issues with Measurement

A

defining true differences and distinguishing these from variations that result from measurement errors

some measurement errors are constant

other errors in measurement are random

43
Q

Measurement Problems: Reliability

A

refers to consistency in the measurement of a variable

44
Q

Tests of Reliability: Test-Retest

A

provides evidence of stable scores

administered once, then administered again to the same subjects under the same conditions

the higher the correlation between the initial test and the retest scores, the higher the reliability

45
Q

Test of Reliability: Split-Half

A

each item in a test is randomly assigned a place in the test

the test is split into two halves, each half considered comparable to the other

46
Q

Test of Reliability: Alternate Forms

A

comparable measures of the same variable are administered to the same subjects at about the same time

the degree of correlation between the two scores is a measure of reliability

47
Q

Test of Reliability: Inter-Judge Agreement

A

two or more judges are trained to observe and score the same phenomenon in the same way

the judges’ independent measures of the same observed phenomenon are correlated

high correlation indicates high reliability

48
Q

What’re the methods increasing reliability?

A

-standardizing administration of the measurement instrument

-adding additional items (test questions) to cancel out random error

-statistically identifying and eliminating items which do not agree with other

49
Q

Tests of Validity: Concurrent Validity

A

the measure used in a study is compared with another instrument presumed to measure the same variable

high correlation of results indicates concurrent validity of the instrument

50
Q

Tests of Validity: Predictive Validity

A

a measure in a study is compared with some predicted future outcome

51
Q

Tests of Validity: Content Validity

A

analysis of an instrument by a group of persons considered expert in the field studied

if the experts judge the test to be a good measurement of what is being studied, the test has content validity

52
Q

Tests of Validity: Construct Validity

A

the degree to which a measure related to other variables expected within a system of theoretical relationships

53
Q

Measures Problem: Scales of Measurement

A

in addition to concern with the measurement problems of reliability and validity, research is also concerned with choosing an appropriate measurement scale

54
Q

Four Categories of Measurement: Nonminal

A

two or more name categories

categories show differences but not the degree of difference

categories have no additive value

measurement involves simply placing subjects in categories and counting the number in each, there are few available statistical procedures

these measures are not highly sensitive in determining differences

55
Q

Four Categories of Measurement: Ordinal

A

the scores show each subject’s position with respect to a particular characteristic

a number of statistics are used with ordinal measurements; these are called non-parametric

56
Q

Four Categories of Measurement: Interval

A

higher-level scale shows ordinal positions with equal intervals between scores

not only ranks data but also uses categories of equal size

57
Q

Four Categories of Measurement: Ratio

A

an interval scale with an absolute zero

a scale where a score of 80 is twice as high as a score of 40 uses the same statistics as interval scales

58
Q

Sampling: Sample

A

part of a large population

the quality of the sample determines the inferences that can be made about the large population from which its drawn

59
Q

Sampling: Population

A

has specific variables in common

60
Q

Sampling: Census

A

a complete count of all relevant members within the sample and population

61
Q

Sampling: Statistic

A

a numerical expression summarizing a sample characteristic of the population from which it is drawn

62
Q

Types of Samples: Probability Sample

A

sample that allows the researcher to specify that each element of the population has a known probability of inclusion

it assures representatives, allows statistical inferences about the population from which it is drawn, and is more precise

63
Q

Probability Sample: Simple Random Sample

A

subjects from a known population are drawn randomly for the sample

each subject has equal probability of inclusion in the sample

64
Q

Probability Sample: Stratified Random Sample

A

subjects are first grouped into strata of interest to the researcher and then drawn randomly from each group

65
Q

Probability Sample: Cluster Random Sample

A

multiple-stage sampling in which successive random samples are drawn from natural groups (clusters) when acquiring a list of all elements of a universe is not possible or too expensive

66
Q

Sampling: Non-Probability Sampling

A

sample in which it is not possible to specify the probability that each element of the population has an equal chance of being included in the sample

67
Q

Non-Probability Sample: Accidental Sample

A

take the first case encountered

68
Q

Non-Probability Sampling: Quota Sample

A

include some cases from each segment of a population

69
Q

Non-Probability Sampling: Purposive Sample

A

purposely draws a sample from a part of the population assumed to have particular knowledge of what is being studied

70
Q

Statistics: Descriptive Statistics

A

computations that describe some characteristics of a group or sample

they enable users of research to summarize information about the group and to make useful comparisons among two or more groups

71
Q

Statistics: Inferential Statistics

A

allow researchers to generalize from a sample to some large population of which the sample is a part

inferential statistics are based on probability theory

72
Q

Descriptive Statistics: Measures of Central Tendency

A

measures the degree to which findings cluster together

73
Q

Measures of Central Tendency: Purpose

A

an average is used to represent all scores in a group, thus giving a concise description of the performance of the group as a whole

allows within group and between group comparisons

74
Q

Measures of Central Tendency: Mean

A

sum of the scores divided by the number of scores; an average

75
Q

Measures of Central Tendency: Median

A

the midpoint of a series of hierarchically ordered scores

half the scores fall above and half fall below the midpoint

76
Q

Measures of Central Tendency: Mode

A

the score or measure occurring most frequently

77
Q

When is mean used?

A

with a symmetrical distribution, when the most stable measure is wanted and when other statistics are to be computed

78
Q

When is median used?

A

when the exact midpoint of a distribution of scores is wanted, when there are extreme scores

79
Q

When is mode used?

A

when a quick and approximate measure is all that is wanted, when the typical value is wanted

80
Q

Measure of Variability: Purpose

A

to determine dispersion or spread of scores around the central tendency

81
Q

Measures of Variability: Measures of Dispersion

A

spread of scores around the average

82
Q

Measures of Dispersion: Ratio

A

the lowest to the highest score

83
Q

Measures of Dispersion: Standard Deviation

A

the most stable measure of variability, it uses squared deviations from the mean degree to which scores are spread or dispersed around the mean

84
Q

Measures of Association: Correlation Coefficient

A

a numerical index of the degree to which two variables measured in interval units are associated with each other

the symbol “r” represents the correlation coefficient

any change in one variable of the pair causes a direct an proportional change in other variable of the pair

85
Q

Correlation Coefficient: Magnitude of Correlation

A

the closer an “r” value gets to 1, the stronger the association r=.80 is stronger than r=.30

86
Q

Correlation Coefficient: Direction of the Association

A

this is indicated by the sign (+) or )-) in front of the “r” coefficient

87
Q

What does (-) mean?

A

indicates a negative or inverse relationships

88
Q

What does (+) mean?

A

indicates a positive or direct association

89
Q

Statistical Tests of Significance: Null Hypothesis

A

the hypothesis that there is “no difference” that is actually subjected to staistical testing

90
Q

Statistical Test of Significance: Type I Error

A

the chance of rejecting the null hypothesis when it should be accepted

91
Q

Statistical Test of Significance: Type II Error

A

the chance of accepting a null hypothesis when it should be rejected

92
Q

Statistical Test of Significance: Statistical Significance

A

an observation or result of an outcome measurement is statistically significant if it falls within the region of “unlikely events” or “unlikely outcomes”

93
Q

Inferential Statistics Definition

A

used to generalize from a sample to some large population from which the sample is drawn

94
Q
A

LMSW Exam (10 decks)

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