Chapter 1
Chapter 1
Human Inquiry and Science
Chapter Outline
Looking for Reality
The Foundations of Social Science
Some Dialectics of Social Research
The Ethics of Social Research
How We Know What We Know
Direct Experience and Observation
Personal Inquiry
Tradition
Authority
Looking for Reality
Our attempts to learn about the world are only partly linked to direct, personal inquiry or experience.
A larger part comes from agreed-on knowledge that others give us, things “everyone knows.”
How do you know that space is cold? Have you ever been in space?
This agreement reality both assists and hinders our attempts to find out for ourselves.
Sources of Secondhand Knowledge
Both provide a starting point for inquiry, but can lead us to start at the wrong point and push us in the wrong direction.
Tradition
Authority
Science and Inquiry
Epistemology is the science of knowing.
Methodology (a subfield of epistemology) might be called the science of finding out.
How do individuals learn all they need to know?
personal experience
Discovery
from what others tell us
all of these choices
Ordinary Human Inquiry
Humans recognize that future circumstances are caused by present ones.
Humans learn that patterns of cause and effect are probabilistic in nature.
Humans aim to answer “what” and “why” questions, and pursue these goals by observing and figuring out.
Inquiry: Errors and Solutions
Inaccurate observations
Measurement devices add precision.
Overgeneralization
Repeat a study to make sure the same results are produced each time.
Inquiry: Errors and Solutions
Selective observation
Make an effort to find cases that do not fit the general pattern.
Illogical Reasoning
Use systems of logic explicitly.
Views of Reality
Premodern - Things are as they seem to be.
Modern - Acknowledgment of human subjectivity.
Postmodern -There is no objective reality to be observed.
A Book
All of these are the same book, but it looks different when viewed from different locations, perspectives, or “points of view.”
Point of View
Wife’s Point of View. There is no question in the wife’s mind as to who is right and rational and who is out of control.
Point of View
Husband’s Point of View. The husband has a very different perception of the same set of events, of course.
Question
In your discussion of measurement with a friend, she argues that what you are trying to measure does not exist and your own point of view will determine what you perceive in measuring. She has which view of reality?
She has the postmodern view of reality
How we can make mistakes
Illogical reasoning!
You have had a “bad run” in poker and you are due to have a good streak.
You got A’s on all tests up until now, and assume that you are going to get a bad grade because the stars are aligned improperly.
You assume that one thing causes another when there is no reason to assume that to be the case.
Foundations of Social Science
The foundations of social science are logic and observation.
A scientific understanding of the world must make sense and correspond to what we observe.
Both are essential to science and relate to the three major aspects of social scientific enterprise: theory, data collection, and data analysis.
Foundations of Social Science
Theory - Systematic explanation for the observations that relate to a particular aspect of life.
Data collection - observation
Data Analysis - the comparison of what is logically expected with what is actually observed.
Social Regularities
Examples of Patterns in social life:
Only people 18 and older can vote.
Only people with a license can drive.
Aggregates
The collective actions and situations of many individuals.
Focus of social science is to explain why aggregated patterns of behavior are regular even when individuals change over time.
Birthrates,United States: 1980– 2002
1982 15.9
1983 15.6
1984 15.6
1985 15.8
1986 15.6
1987 15.7
1988 16.0
1989 16.4
1990 16.7
1991 16.2
1992 15.8
1993 15.4
1994 15.0
1995 14.6
1996 14.4
1997 14.2
1998 14.3
1999 14.2
2000 14.4
2001 14.1
2002 13.9
Question
Social research aims to find regularity in social life.
Meaning, we are attempting to explain things by looking at commonalities.
What’s in a Name (Label)
Variable
Logical groupings of attributes.
Attribute
Characteristics or qualities that describe an object.
Types of Variables
Independent variable
A variable that is presumed to cause or determine a dependent variable.
Dependent variable
A variable that is assumed to depend on or is caused by another variable.
Confounding variables
Those variables that mess every thing up!
Variable Language
Relationship Between Two Variables
Education and Racial Prejudice
Question
What would the following categories be? married, never married, widowed, separated, and divorced. These categories are known as
variables.
attributes.
variable categories.
units of analysis.
theoretical elements.
Approaches to Social Research
Idiographic -Seeks to fully understand the causes of what happened in a single instance.
Nomothetic—Seeks to explain a class of situations or events rather than a single one.
Examples
Idiographic: “He’s like that because his father and mother kept giving him mixed signals.The fact that his family moved seven times by the time he was 12 years old didn’t help. Moreover, his older brother is exactly the same and probably served as a role model.”
Nomothetic:“Teenage boys are like that.”
Approaches to Social Research
Induction – From specific observations to the discovery of a pattern among all the given events.
Deduction - From a pattern that might be logically expected to observations that test whether the pattern occurs.
The Wheel of Science
Approaches to Social Research
Qualitative Data – Nonnumerical data.
Quantitative Data -Numerical data. Makes observations more explicit and makes it easier to aggregate, compare, and summarize data.
Approaches to Social Research
Pure Research - Sometimes justified in terms of gaining “knowledge for knowledge’s sake.”
Applied Research – Putting research into practice.
Lets talk about people:
Ethical Guidelines of Social Research
Two Basic Guidelines:
Participation should be voluntary.
Social research must bring no harm to research subjects.
Chapter 2
Paradigms (No not 20 cents), Theory, And Research
Chapter Outline
Introduction
Some Social Science Paradigms
Elements of Social Theory
Two Logical Systems Revisited
Deductive Theory Construction
Inductive Theory Construction
The Links Between Theory and Research
Theory and Research
Theory functions three ways in research:
Theories prevent our being taken in by flukes.
Theories make sense of observed patterns in ways that can suggest other possibilities.
Theories can direct research efforts, pointing toward likely discoveries through empirical observation.
But wait, I have a theory!
What do theories seek to provide?
Headaches for students
Something for us to disprove
The ways things are
logical explanations
Theories seek to provide logical explanations.
Paradigms
(Do you have change for my Paradigms)
A model or framework for observation and understanding, which shapes both what we see and how we understand it.
The conflict paradigm causes us to see social behavior one way, the interactionist paradigm causes us to see it differently.
We can see new ways of seeing and explaining things when we step outside our paradigm.
Social Science Paradigms: Macrotheory
Macrotheory deals with large, aggregate entities of society or whole societies.
Struggle between economic classes, international relations
Social Science Paradigms: Microtheory
Microtheory deals with issues at the level of individuals and small groups.
Dating behavior, jury deliberations, student faculty interactions
Social Science Paradigms: Social Darwinism
Comte’s view that science would replace religion and metaphysics by basing knowledge on observations.
Comte coined positivism, in contrast to what he regarded as negative elements in the Enlightenment.
Social Science Paradigms: Conflict
Marx suggested social behavior could be seen as the process of conflict:
Attempt to dominate others.
Attempt to avoid domination.
Social Science Paradigms: Symbolic Interactionism
Interactions revolve around individuals reaching understanding through language and other systems.
Can lend insights into the nature of interactions in ordinary social life.
Social Science Paradigms: Ethnomethodology
People are continuously trying to make sense of the life they experience.
One technique is to break the rules and violate people’s expectations.
Social Science Paradigms: Structural Functionalism
A social entity, such as an organization, can be viewed as an organism.
A social system is made up of parts, each of which contributes to the functioning of the whole.
This view looks for the “functions” served by the various components of society.
Social Science Paradigms: Feminism
Focuses on gender differences and how they relate to the rest of social organization.
Draws attention to the oppression of women in many societies, and sheds light on all kinds of oppression.
Women’s Ways of Knowing
5 perspectives on knowing that challenge the view of inquiry as straightforward:
Silence: Some women feel isolated from knowledge, their lives are largely determined by external authorities.
Women’s Ways of Knowing
Received knowledge: Women feel comfortable taking in knowledge from external authorities.
Subjective knowledge: Open to the possibility of personal, subjective knowledge, including intuition.
Women’s Ways of Knowing
Procedural knowledge: Learning how to gain knowledge through objective procedures.
Constructed knowledge: Women view knowledge as contextual, experience themselves as creators of knowledge and value subjective and objective ways of knowing.
Social Science Paradigms: Critical Race Theory
In the mid-1970s, civil rights activists and social scientists began the codification of a paradigm based on a commitment to racial justice.
The concept of interest convergence suggests that laws will only be changed to benefit African Americans if those changes further the interests of whites.
Asch Experiment
Purpose was to see whether subjects were swayed by pressure to go along with an incorrect answer.
Initial experiments, found that a little over 1/3 of subjects were.
Elements of Social Theory
Theories are systematic sets of interrelated statements intended to explain some aspect of social life.
A paradigm offers a way of looking, a theory aims at explaining what we see.
In social research, observation refers to seeing, hearing, and—less commonly—touching.
Elements of Social Theory
Social scientists use fact to refer to a phenomenon that has been observed.
Scientists organize many facts under “rules” called laws.
A variable is a special kind of concept.
Axioms or postulates are assertions, taken to be true, on which a theory is grounded.
Elements of Social Theory
Propositions are specific conclusions, derived from the axiomatic groundwork, about the relationships among concepts.
A hypothesis is a specified testable expectation about empirical reality that follows from a more general proposition.
Research is designed to test hypotheses.
So, lets break it down in to simple terms
Theories are systematic sets of interrelated statements intended to explain some aspect of social life (or other aspect of a phenomenon for that matter!).
Traditional Model of Science
There are three main elements in the traditional model of science:
Theory
Operationalization - Developing operational definitions, or specifying the exact operations involved in measuring a variable.
Observation - Looking at the world and making measurements of what is seen.
Operational Definition
The concrete and specific definition of something in terms of the operations by which observations are to be categorized.
The Traditional Image of Science
The deductive model of scientific inquiry begins with a sometimes vague or general question, which is subjected to a process of specification, resulting in hypotheses that can be tested through empirical observations.
Null Hypothesis
In connection with hypothesis testing and tests of statistical significance, that hypothesis that suggests there is no relationship among the variables under study.
You may conclude that the variables are related after having statistically rejected the null hypothesis. (Yeah, but what does it really tell you?)
Linking Social Scientific Theory and Research
Deduction - Deriving expectations or hypotheses from theories.
Induction - Developing generalizations from specific observations.
Deductive Theory Construction
Pick a topic.
Specify a range: Will your theory apply to all of human social life, only certain ages?
Identify major concerns and variables.
Find out what is known about the relationships among the variables.
Reason from those propositions to the topic you are interested in.
Inductive Theory Construction
social scientists construct a theory through the inductive method by observing aspects of social life and seeking to discover patterns that point to relatively universal principles.
Barney Glaser and Anselm Strauss (1967) used the term grounded theory for this method.
Field research, direct observation of events in progress, is frequently used to develop theories through observation.
1. The three main elements of the traditional model of science are
theory, operationalization, observation.
operationalization, hypothesis testing, theory.
observation, experimentation, operationalization.
theory, observation, hypothesis testing.
experimentation, hypothesis testing, theory.
Answer: A
The three main elements of the traditional model of science are theory, operationalization, observation.
2. Which of the following is the best example of a hypothesis?
The greater the level of education, the greater the tolerance for alternative lifestyles.
Socialization in childhood has a significant impact on adolescent gender-role identity.
There are more female than male college students.
Religiosity equals frequency of church attendance and praying.
Actions are based on perceived costs and rewards.
Answer: A
The following is the best example of a hypothesis: The greater the level of education, the greater the tolerance for alternative lifestyles.
Chapter 3
The Ethics and Politics of Social Research
Chapter Outline
Introduction
Ethical Issues in Social Research
Two Ethical Controversies
The Politics of Social Research
Ethical Issues in Social Research
Voluntary participation
No harm to participants
Anonymity and confidentiality
Ethical Issues in Social Research
Deception must be justified by compelling scientific concerns.
Researchers must be honest about their findings and research.
Question
Which constraints must be placed on social research for it to be considered realistic?
scientific constraints
administrative constraints
ethical constraints
all of these choices
Answer: D
Scientific, administrative and ethical constraints must be placed on social research for it to be considered realistic.
Informed Consent
Subjects in a study must base their voluntary participation on a full understanding of the possible risks involved.
Anonymity
The researcher cannot identify a given response with a given respondent.
Confidentiality
Researcher can identify a given person's responses but promises not to do so publicly.
Debriefing
Interviews to discover any problems generated by the research experience so they can be corrected.
Ethical Issues in Social Research
Institutional Review Boards
Review research proposals involving humans so they can guarantee the rights and interests are protected.
Ethical Issues in Social Research
Professional Codes of Ethics
Most professional associations have formal codes of conduct that describe acceptable and unacceptable professional behavior.
Ethical Controversy:
Laud Humphreys
Study of homosexual behavior in public restrooms.
Lied to participants by telling them he was a voyeur-participant.
Traced participants to their home and interviewed them under false pretenses.
Ethical Controversy: Stanley Milgram
Study of human obedience.
Subjects had role of "teacher" and administered a shock to "pupils".
Pupils were actually part of the experiment.
Ethics and Politics of Social Research
Ethics deals mostly with methods used in research.
Politics deals with the substance and use of research.
There are no formal codes of accepted political conduct.
Politics in Perspective
Science is not untouched by politics.
Science proceeds in the midst of political controversy and hostility.
Politics in Perspective
Awareness of ideologies enriches the study and practice of social research methods.
While researchers should not let their values interfere with their research, this does not mean that researchers should not express both their scientific expertise and personal values.
Social Science Paradigms: Symbolic Interactionism
Interactions revolve around individuals reaching understanding through language and other systems.
Can lend insights into the nature of interactions in ordinary social life.
Social Science Paradigms: Ethnomethodology
People are continuously trying to make sense of the life they experience.
One technique is to break the rules and violate people’s expectations.
Social Science Paradigms: Structural Functionalism
A social entity, such as an organization, can be viewed as an organism.
A social system is made up of parts, each of which contributes to the functioning of the whole.
This view looks for the “functions” served by the various components of society.
Social Science Paradigms: Feminism
Focuses on gender differences and how they relate to the rest of social organization.
Draws attention to the oppression of women in many societies, and sheds light on all kinds of oppression.
Social Science Paradigms: Critical Race Theory
In the mid-1970s, civil rights activists and social scientists began the codification of a paradigm based on a commitment to racial justice.
The concept of interest convergence suggests that laws will only be changed to benefit African Americans if those changes further the interests of whites.
Asch Experiment
Purpose was to see whether subjects were swayed by pressure to go along with an incorrect answer.
Initial experiments, found that a little over 1/3 of subjects were.
Elements of Social Theory
Theories are systematic sets of interrelated statements intended to explain some aspect of social life.
A paradigm offers a way of looking, a theory aims at explaining what we see.
In social research, observation refers to seeing, hearing, and—less commonly—touching.
Elements of Social Theory
Social scientists use fact to refer to a phenomenon that has been observed.
Scientists organize many facts under “rules” called laws.
A variable is a special kind of concept.
Axioms or postulates are assertions, taken to be true, on which a theory is grounded.
Elements of Social Theory
Propositions are specific conclusions, derived from the axiomatic groundwork, about the relationships among concepts.
A hypothesis is a specified testable expectation about empirical reality that follows from a more general proposition.
Research is designed to test hypotheses.
So, lets break it down in to simple terms
Theories are systematic sets of interrelated statements intended to explain some aspect of social life (or other aspect of a phenomenon for that matter!).
Traditional Model of Science
There are three main elements in the traditional model of science:
Theory
Operationalization - Developing operational definitions, or specifying the exact operations involved in measuring a variable.
Observation - Looking at the world and making measurements of what is seen.
Operational Definition
The concrete and specific definition of something in terms of the operations by which observations are to be categorized.
The Traditional Image of Science
The deductive model of scientific inquiry begins with a sometimes vague or general question, which is subjected to a process of specification, resulting in hypotheses that can be tested through empirical observations.
Null Hypothesis
In connection with hypothesis testing and tests of statistical significance, that hypothesis that suggests there is no relationship among the variables under study.
You may conclude that the variables are related after having statistically rejected the null hypothesis. (Yeah, but what does it really tell you?)
Linking Social Scientific Theory and Research
Deduction - Deriving expectations or hypotheses from theories.
Induction - Developing generalizations from specific observations.
Deductive Theory Construction
Pick a topic.
Specify a range: Will your theory apply to all of human social life, only certain ages?
Identify major concerns and variables.
Find out what is known about the relationships among the variables.
Reason from those propositions to the topic you are interested in.
Inductive Theory Construction
social scientists construct a theory through the inductive method by observing aspects of social life and seeking to discover patterns that point to relatively universal principles.
Barney Glaser and Anselm Strauss (1967) used the term grounded theory for this method.
Field research, direct observation of events in progress, is frequently used to develop theories through observation.
2. Which of the following is the best example of a hypothesis?
The greater the level of education, the greater the tolerance for alternative lifestyles.
Socialization in childhood has a significant impact on adolescent gender-role identity.
There are more female than male college students.
Religiosity equals frequency of church attendance and praying.
Actions are based on perceived costs and rewards.
Answer: A
The following is the best example of a hypothesis: The greater the level of education, the greater the tolerance for alternative lifestyles.
Chapter 3
The Ethics and Politics of Social Research
Chapter Outline
Introduction
Ethical Issues in Social Research
Two Ethical Controversies
The Politics of Social Research
Ethical Issues in Social Research
Voluntary participation
No harm to participants
Anonymity and confidentiality
Ethical Issues in Social Research
Deception must be justified by compelling scientific concerns.
Researchers must be honest about their findings and research.
Question
Which constraints must be placed on social research for it to be considered realistic?
scientific constraints
administrative constraints
ethical constraints
all of these choices
Answer: D
Scientific, administrative and ethical constraints must be placed on social research for it to be considered realistic.
Informed Consent
Subjects in a study must base their voluntary participation on a full understanding of the possible risks involved.
Anonymity
The researcher cannot identify a given response with a given respondent.
Confidentiality
Researcher can identify a given person's responses but promises not to do so publicly.
Question
______________ is a norm in which subjects base their voluntary participation in research projects on a full understanding of the possible risks involved.
research participation
the Hawthorne effect
informed consent
the code of ethics
none of these choices
Answer: C
Informed consent is a norm in which subjects base their voluntary participation in research projects on a full understanding of the possible risks involved.
Debriefing
Interviews to discover any problems generated by the research experience so they can be corrected.
Ethical Issues in Social Research
Institutional Review Boards
Review research proposals involving humans so they can guarantee the rights and interests are protected.
Ethical Issues in Social Research
Professional Codes of Ethics
Most professional associations have formal codes of conduct that describe acceptable and unacceptable professional behavior.
Ethical Controversy:
Laud Humphreys
Study of homosexual behavior in public restrooms.
Lied to participants by telling them he was a voyeur-participant.
Traced participants to their home and interviewed them under false pretenses.
Ethical Controversy: Stanley Milgram
Study of human obedience.
Subjects had role of "teacher" and administered a shock to "pupils".
Pupils were actually part of the experiment.
Ethics and Politics of Social Research
Ethics deals mostly with methods used in research.
Politics deals with the substance and use of research.
There are no formal codes of accepted political conduct.
Politics in Perspective
Science is not untouched by politics.
Science proceeds in the midst of political controversy and hostility.
Politics in Perspective
Awareness of ideologies enriches the study and practice of social research methods.
While researchers should not let their values interfere with their research, this does not mean that researchers should not express both their scientific expertise and personal values.
1. Ethics are not a consideration in which one of the following fields of research? Or do ethics enter in all of these fields?
natural sciences
psychology
medical
sociology
ethics enter in all of them
2. The major justification the social scientist has for requesting participation in a study is that
it may help the respondent.
it may help all humanity.
it may help the social scientist.
it may help government officials make policy decisions.
it may help improve the educational system.
Answer: B
The major justification the social scientist has for requesting participation in a study is that: it may help all humanity.
Chapter 4
Research Design
Chapter Outline
Introduction
Three Purposes of Research
The Logic of Nomothetic Explanation
Necessary and Sufficient Causes
Chapter Outline
Units of Analysis
The Time Dimension
How to Design a Research Project
The Research Proposal
Three Purposes of Research
Exploration
Description
Explanation
Purpose of Exploratory Studies
Satisfy researcher’s curiosity and desire for better understanding.
Test the feasibility of undertaking a more extensive study.
Develop methods to be employed in a subsequent study.
Question
Scientific inquiry comes down to:
making observations
interpreting what you’ve observed
both a and b
none of these choices
Answer: C
Scientific inquiry comes down to making observations and interpreting what you’ve observed.
The Logic of Nomothetic Explanation
In this model, we try to find independent variables that account for the variations in a given phenomenon.
This contrasts with the idiographic model, in which we seek a complete, in-depth understanding of a single case.
Criteria for Nomothetic Causality
A statistical correlation between the two variables.
The cause takes place before the effect.
There is no third variable that can explain away the observed correlation as spurious.
Correlation
A relationship between two variables such that
changes in one are associated with changes in the other
particular attributes of one variable are associated with particular attributes of the other.
Correlation in and of itself does not constitute a causal relationship between the two variables, but it is one criterion of causality.
Spurious Relationships
Relationships that aren't genuine.
A coincidental statistical correlation between two variables, shown to be caused by some third variable.
False Criteria for Nomothetic Causality
Research can determine some causes, but it cannot determine complete causation.
Exceptions do not disprove a causal relationship.
Causal relationships can be true even if they don’t apply in a majority of cases.
Question
A ____________ is an empirical relationship between two variables such that changes in one are associated with changes in the other.
nomothetic explanation
regression analysis
correlation
spurious relationship
Answer: C
A correlation is an empirical relationship between two variables such that changes in one are associated with changes in the other.
Example of a Spurious Causal Relationship
Necessary and Sufficient Causes
Necessary cause - a condition that must be present for the effect to follow.
Sufficient cause - condition that if present, guarantees the effect in question.
Causes that are both necessary and sufficient are the most satisfying outcome in research.
Necessary Cause
Sufficient Cause
Units of Analysis
What or whom to study:
Individuals
Groups
Organizations
Social artifacts - Any product of social beings or their behavior.
Units of Analysis and Faulty Reasoning
Ecological fallacy – assuming something learned about an ecological unit says something about the individuals in the unit.
Reductionism – Reducing something to a simple explanation when in reality it is complex.
Sociobiology
A paradigm based in the view that social behavior can be explained in terms of genetic characteristics and behavior.
Time Studies
Cross-sectional studies
Observations of a sample, or cross-section of a population or phenomena that are made at one point in time. ( U.S. Census)
Longitudinal Studies
Permits observations of the same phenomenon over an extended period. (field-research projects)
Time Studies
Trend Studies
A type of longitudinal study that examines change within a population over time. (comparison of U.S. Census over a period of decades)
Longitudinal Studies
Cohort studies
Examines specific subpopulations, or cohorts, as they change over time.
Longitudinal Studies
Panel Study
Examines the same set of people each time. (interview same sample of voters every month during an election campaign).
Age and Political Liberalism
Comparing Types
of Longitudinal Studies
Variable: religious affiliation.
A trend study might look at shifts in U.S. religious affiliations over time, as the Gallup Poll does on a regular basis.
A cohort study might follow religious affiliations among “the Depression generation,” people aged 20 to 30 in 1932.
A panel study could start with a sample of the whole population or a special subset and study those specific individuals over time.
How to Design a Research Project
Define the purpose of your project.
Specify exact meanings for the concepts you want to study.
Choose a research method.
Decide how to measure the results.
How to Design a Research Project
Decide whom or what to study.
Collect empirical data.
Process the data.
Analyze the data.
Report your findings.
Elements of a Research Proposal
Problem or objective
Literature review
Subjects for study
Measurement
Elements of a Research Proposal
Data-collection methods
Analysis
Schedule
Budget
Chapter 5
Conceptualization, Operationalization, and Measurement
Chapter Outline
Introduction
Measuring Anything That Exists
Conceptualization
Definitions in Descriptive and Explanatory Studies
Operationalization Choices
Criteria of Measurement Quality
A Quandary Revisited
Measurement
Careful, deliberate observations of the real world for the purpose of describing objects and events in terms of the attributes composing a variable.
Conceptualization
Process of specifying what we mean when we use particular terms.
Produces an agreed upon meaning for a concept for the purposes of research.
Describes the indicators we'll use to measure the concept and the different aspects of the concept.
Indicators and Dimensions
An indicator is a sign of the presence or absence of the concept we’re studying.
Dimension is a specifiable aspect of a concept.
“Religiosity” might be specified in terms of a belief dimension, a ritual dimension, a devotional dimension, a knowledge dimension, and so forth.
Interchangeability of Indicators
If several different indicators all represent the same concept, all of them will behave the same way the concept would behave if it were real and could be observed.
If women are more compassionate, we should be able to observe that using a reasonable measure of compassion.
If women are more compassionate only on some indicators, we should see if the indicators represent different dimensions of compassion.
Specification of Concepts
The specification of concepts in scientific inquiry depends on nominal and operational definitions.
A nominal definition is simply assigned to a term without any claim that the definition represents a “real” entity.
An operational definition specifies precisely how a concept will be measured—that is, the operations we’ll perform.
Definitions
Real - mistakes a construct for a real entity.
Nominal - assigned to a term without a claim that the definition represents a "real" entity.
Operational definitions - Specifies how a concept will be measured.
From Concept to Measurement
Progression from what a term means to measurement in a scientific study:
Conceptualization
Nominal Definition
Operational Definition
Measurements in the Real World
Nominal Measure
A level of measurement describing a variable that has attributes that are merely different, as distinguished from ordinal, interval, or ratio measures.
Gender is an example of a nominal measure.
Ordinal Measure
A level of measurement describing a variable with attributes we can rank-order along some dimension.
An example is socioeconomic status as composed of the attributes high, medium, low.
Interval Measures
A level of measurement describing a variable whose attributes are rank-ordered and have equal distances between adjacent attributes.
Ratio Measures
A level of measurement describing a variable with attributes that have all the qualities of nominal, ordinal, and interval measures and in addition are based on a “true zero” point.
Question
Which of the following are examples of nominal measures?
gender
religious affiliation
political party affiliation
birthplace
all of these choices
Answer: E
Gender, religious affiliation, political party affiliation and birthplace are examples of nominal measures.
Kaplan’s Classes
Things Scientists Measure
Direct observables - things that can be observed simply and directly.
Indirect observables - things that require more subtle observations.
Constructs - based on observations that cannot be observed.
Measurement Quality
Precision and accuracy
Reliability
Validity
Reliability
That quality of measurement method that suggests that the same data would have been collected each time in repeated observations of the same phenomenon.
In the context of a survey, we would expect that the question “Did you attend religious services last week?” would have higher reliability than the question “About how many times have you attended religious services in your life?”
Tests for Checking Reliability
Test-retest method - take the same measurement more than once.
Split-half method - make more than one measurement of a social concept (prejudice).
Use established measures.
Check reliability of research-workers.
Validity
A term describing a measure that accurately reflects the concept it is intended to measure.
Example: IQ would seem a more valid measure of intelligence than the number of hours spent in the library.
Though the ultimate validity of a measure can never be proved, we may agree to its relative validity on the basis of face validity, criterion validity, content validity, construct validity, internal validation, and external validation.
Face Validity
That quality of an indicator that makes it seem a reasonable measure of some variable.
That the frequency of attendance at religious services is some indication of a person’s religiosity seems to make sense without a lot of explanation.
Construct and Content Validity
Construct Validity
The degree to which a measure relates to other variables as expected within a system of theoretical relationships.
Content Validity
Refers to how much a measure covers the range of meanings included within a concept.
Question
_____________ is the degree to which a measure covers the range of meanings included within a concept.
construct validity
criterion-related validity
face validity
content validity
Answer: D
Content Validity is the degree to which a measure covers the range of meanings included within a concept.
An Analogy to Validity and Reliability
A good measurement technique should be both valid (measuring what it is intended to measure) and reliable (yielding a given measurement dependably).
Quick Quiz
1. In social research, the process of coming to an agreement about what terms mean is ______________.
hypotheses
conceptualization
guesses
variables
Answer: B
In social research, the process of coming to an agreement about what terms mean is conceptualization.
4. A level of measurement describing a variable whose attributes are rank-ordered and have equal distances between adjacent attributes are ________.
ratio measures
interval measures
nominal measures
ordinal measures
Answer: B
A level of measurement describing a variable whose attributes are rank-ordered and have equal distances between adjacent attributes are interval measures.
Units of Analysis and Faulty Reasoning
Ecological fallacy – assuming something learned about an ecological unit says something about the individuals in the unit.
Reductionism – Reducing something to a simple explanation when in reality it is complex.
Sociobiology
A paradigm based in the view that social behavior can be explained in terms of genetic characteristics and behavior.
Time Studies
Cross-sectional studies
Observations of a sample, or cross-section of a population or phenomena that are made at one point in time. ( U.S. Census)
Longitudinal Studies
Permits observations of the same phenomenon over an extended period. (field-research projects)
Time Studies
Trend Studies
A type of longitudinal study that examines change within a population over time. (comparison of U.S. Census over a period of decades)
Longitudinal Studies
Cohort studies
Examines specific subpopulations, or cohorts, as they change over time.
Longitudinal Studies
Panel Study
Examines the same set of people each time. (interview same sample of voters every month during an election campaign).
Comparing Types
of Longitudinal Studies
Variable: religious affiliation.
A trend study might look at shifts in U.S. religious affiliations over time, as the Gallup Poll does on a regular basis.
A cohort study might follow religious affiliations among “the Depression generation,” people aged 20 to 30 in 1932.
A panel study could start with a sample of the whole population or a special subset and study those specific individuals over time.
How to Design a Research Project
Define the purpose of your project.
Specify exact meanings for the concepts you want to study.
Choose a research method.
Decide how to measure the results.
How to Design a Research Project
Decide whom or what to study.
Collect empirical data.
Process the data.
Analyze the data.
Report your findings.
Elements of a Research Proposal
Problem or objective
Literature review
Subjects for study
Measurement
Elements of a Research Proposal
Data-collection methods
Analysis
Schedule
Budget
Chapter 5
Conceptualization, Operationalization, and Measurement
Chapter Outline
Introduction
Measuring Anything That Exists
Conceptualization
Definitions in Descriptive and Explanatory Studies
Operationalization Choices
Criteria of Measurement Quality
A Quandary Revisited
Measurement
Careful, deliberate observations of the real world for the purpose of describing objects and events in terms of the attributes composing a variable.
Conceptualization
Process of specifying what we mean when we use particular terms.
Produces an agreed upon meaning for a concept for the purposes of research.
Describes the indicators we'll use to measure the concept and the different aspects of the concept.
Indicators and Dimensions
An indicator is a sign of the presence or absence of the concept we’re studying.
Dimension is a specifiable aspect of a concept.
“Religiosity” might be specified in terms of a belief dimension, a ritual dimension, a devotional dimension, a knowledge dimension, and so forth.
Specification of Concepts
The specification of concepts in scientific inquiry depends on nominal and operational definitions.
A nominal definition is simply assigned to a term without any claim that the definition represents a “real” entity.
An operational definition specifies precisely how a concept will be measured—that is, the operations we’ll perform.
Definitions
Operational definitions - Specifies how a concept will be measured.
From Concept to Measurement
Progression from what a term means to measurement in a scientific study:
Conceptualization
Nominal Definition
Operational Definition
Measurements in the Real World
Nominal Measure
A level of measurement describing a variable that has attributes that are merely different, as distinguished from ordinal, interval, or ratio measures.
Gender is an example of a nominal measure.
Ordinal Measure
A level of measurement describing a variable with attributes we can rank-order along some dimension.
An example is socioeconomic status as composed of the attributes high, medium, low.
Interval Measures
A level of measurement describing a variable whose attributes are rank-ordered and have equal distances between adjacent attributes.
Ratio Measures
A level of measurement describing a variable with attributes that have all the qualities of nominal, ordinal, and interval measures and in addition are based on a “true zero” point.
Kaplan’s Classes
Things Scientists Measure
Direct observables - things that can be observed simply and directly.
Indirect observables - things that require more subtle observations.
Constructs - based on observations that cannot be observed.
Measurement Quality
Precision and accuracy
Reliability
Validity
Reliability
That quality of measurement method that suggests that the same data would have been collected each time in repeated observations of the same phenomenon.
In the context of a survey, we would expect that the question “Did you attend religious services last week?” would have higher reliability than the question “About how many times have you attended religious services in your life?”
Tests for Checking Reliability
Test-retest method - take the same measurement more than once.
Split-half method - make more than one measurement of a social concept (prejudice).
Use established measures.
Check reliability of research-workers.
Validity
A term describing a measure that accurately reflects the concept it is intended to measure.
Example: IQ would seem a more valid measure of intelligence than the number of hours spent in the library.
Though the ultimate validity of a measure can never be proved, we may agree to its relative validity on the basis of face validity, criterion validity, content validity, construct validity, internal validation, and external validation.
Face Validity
That quality of an indicator that makes it seem a reasonable measure of some variable.
That the frequency of attendance at religious services is some indication of a person’s religiosity seems to make sense without a lot of explanation.
Construct and Content Validity
Construct Validity
The degree to which a measure relates to other variables as expected within a system of theoretical relationships.
Content Validity
Refers to how much a measure covers the range of meanings included within a concept.
An Analogy to Validity and Reliability
A good measurement technique should be both valid (measuring what it is intended to measure) and reliable (yielding a given measurement dependably).
Chapter 6
Indexes, Scales, and Typologies
Chapter Outline
Introduction
Indexes versus Scales
Index Construction
Scale Construction
Typologies
Index and Scale
Index
Constructed by accumulating scores assigned to individual attributes.
Scale
Constructed by assigning scores to patterns of responses, recognizing that some items reflect a weak degree of the variable while others reflect something stronger.
Question
In order to achieve broad coverage of various dimensions of a concept, researchers need to make____________.
single observations
field research observations
multiple observations
none of these choices
Answer: C
In order to achieve broad coverage of various dimensions of a concept, researchers need to make multiple observations.
Index and Scale: Similarities
Both are ordinal measures of variables.
Both rank order units of analysis in terms of specific variables.
Both are measurements based on more than one data item.
Index and Scale:
Scoring Differences
Index
Accumulate scores assigned to individual attributes.
Scale
Assign scores to patterns of responses.
Question
Which of the following are common characteristics shared by both indexes and scales?
both are ordinal measures
both rank-order units in terms of specific variables
both are composite measures
all of these choices
Answer: D
The following are common characteristics shared by both indexes and scales: both are ordinal measure, both rank-order units in terms of specific variables, and both are composite measures.
Index-Construction Logic
Below are political actions with similar degrees of activism. To create an index we might give people 1 point for each of the actions they’ve taken.
Scale-Construction Logic
Below are political actions with different degrees of activism. To construct a scale we might score people according to which of the ideal patterns most closely describes them.
Constructing an Index
Select items for a composite index.
Examine empirical relationships.
Assign scores for responses.
Handle missing data.
Validate the index.
Selecting Items
Criteria
Face (logical) validity
Unidimensionality
General or specific
Variance
Empirical Relationships
Established when respondents’ answers to one question help predict how they will answer other questions.
If two items are empirically related, we can argue that each reflects the same variable, and both can be included in the same index.
Assign Scores for Responses
Two basic decisions:
Decide the desirable range of the index scores.
Decide whether to give each item in the index equal weight or different weights.
Ways to Handle Missing Data
Exclude cases with missing data from the construction of the index and the analysis.
Treat missing data as one of the available responses.
Analyze missing data to interpret the meaning.
Validate the Index
Item Analysis - internal validation.
External validation - ranking of groups on the index should predict the ranking of groups in answering similar or related questions.
Techniques of Scale Construction
Likert scaling - uses standardized response categories.
Semantic differential -asks respondents to rank answers between two extremes.
Semantic Differential: Feelings about Musical Selections
The semantic differential asks respondents to describe something or someone in terms of opposing adjectives.
Chapter 7
The Logic Of Sampling
Chapter Outline
Introduction
A Brief History of Sampling
Nonprobability Sampling
The Theory and Logic of Probability Sampling
Chapter Outline
Populations and Sampling Frames
Types of Sampling Designs
Multistage Cluster Sampling
Probability Sampling in Review
Political Polls and Survey Sampling
In the 2004 Presidential election, pollsters generally agreed that the election was “too close to call”.
To gather this information, they interviewed fewer than 2,000 people.
Election Eve Polls - U.S. Presidential Candidates, 2004
Election Eve Polls - U.S. Presidential Candidates, 2004
Election Eve Polls - U.S. Presidential Candidates, 2004
Bush Approval: Raw Poll Data
Observation and Sampling
Polls and other forms of social research rest on observations.
The task of researchers is to select the key aspects to observe (sample).
Generalizing from a sample to a larger population is called probability sampling and involves random selection.
Nonprobability Sampling
Technique in which samples are selected in a way that is not suggested by probability theory.
Examples include reliance on available subjects as well as purposive (judgmental), quota, and snowball sampling.
Types of Nonprobability Sampling
Reliance on available subjects:
Only justified if less risky sampling methods are not possible.
Researchers must exercise caution in generalizing from their data when this method is used.
Types of Nonprobability Sampling
Purposive or judgmental sampling
Selecting a sample based on knowledge of a population, its elements, and the purpose of the study.
Used when field researchers are interested in studying cases that don’t fit into regular patterns of attitudes and behaviors
Types of Nonprobability Sampling
Snowball sampling
Appropriate when members of a population are difficult to locate.
Researcher collects data on members of the target population she can locate, then asks them to help locate other members of that population.
Types of Nonprobability Sampling
Quota sampling
Begin with a matrix of the population.
Data is collected from people with the characteristics of a given cell.
Each group is assigned a weight appropriate to their portion of the population.
Data should represent the total population.
Informant
Someone who is well versed in the social phenomenon that you wish to study and who is willing to tell you what he or she knows about it.
Probability Sampling
Used when researchers want precise, statistical descriptions of large populations.
A sample of individuals from a population must contain the same variations that exist in the population.
Populations and Sampling Frames
Findings based on a sample represent the aggregation of elements that compose the sampling frame.
Sampling frames do not always include all the elements their names imply.
All elements must have equal representation in the frame.
A Population of 100 Folks
Sampling aims to reflect the characteristics and dynamics of large populations.
Let’s assume our total population only has 100 members.
Sample of Convenience: Easy but Not Representative
Types of Sampling Designs
Simple random sampling (SRS)
Systematic sampling
Stratified sampling
Representativeness
Representativeness - Quality of a sample having the same distribution of characteristics as the population from which it was selected.
EPSEM - Equal probability of selection method. A sample design in which each member of a population has the same chance of being selected into the sample.
Population
The theoretically specified aggregation of study elements.
Study population - Aggregation of elements from which the sample is actually selected.
Element - Unit about which information is collected and that provides the basis of analysis.
Random selection
Each element has an equal chance of selection independent of any other event in the selection process.
Sampling unit
Element or set of elements considered for selection in some stage of sampling.
Parameter
Summary description of a given variable in a population.
A Population of 10 People with $0–$9
The Sampling Distribution of Samples of 1
In this example, the mean amount of money these people have is $4.50 ($45/10).
If we picked 10 different samples of 1 person each, our “estimates” of the mean would range all across the board.
Sampling Distributions
Sampling Distributions
Sampling Distributions
Sampling Distributions
Range of Possible Sample Study Results
Shifting to a more realistic example, let’s assume that we want to sample student attitudes concerning a proposed conduct code.
Let’s assume 50% of the student body approves and 50% disapproves - though the researcher doesn’t know that.
Results Produced by Three Hypothetical Studies
Assuming a large student body, let’s suppose we selected three different samples, each of substantial size.
We would not expect those samples to perfectly reflect attitudes in the whole student body, but they should come close.
Statistic
Summary description of a variable in a sample.
Sampling Error
The degree of error to be expected of a given sample design.
Confidence Level
The estimated probability that a population parameter lies within a given confidence interval.
Thus, we might be 95% confident that between 35 and 45% of all voters favor Candidate A.
Confidence interval - The range of values within which a population parameter is estimated to lie.
Sampling Frame
That list or quasi list of units composing a population from which a sample is selected.
If the sample is to be representative of the population, it is essential that the sampling frame include all (or nearly all) members of the population.
The Sampling Distribution
If we were to select a large number of good samples, we would expect them to cluster around the true value (50%), but given enough such samples, a few would fall far from the mark.
Review of Populations and Sampling Frames: Guidelines
Findings based on a sample represent only the aggregation of elements that compose the sampling frame.
Sampling frames do not include all the elements their names might imply. Omissions are inevitable.
To be generalized, all elements must have equal representation in the frame.
Simple Random Sampling
Feasible only with the simplest sampling frame.
Not the most accurate method available.
Systematic Sampling
Slightly more accurate than simple random sampling.
Arrangement of elements in the list can result in a biased sample.
Sampling ratio
Proportion of elements in the population that are selected.
Stratification
Grouping of units composing a population into homogenous groups before sampling.
This procedure, which may be used in conjunction with simple random, systematic, or cluster sampling, improves the representativeness of a sample, at least in terms of the stratification variables.
Stratified Sampling
Rather than selecting sample for population at large, researcher draws from homogenous subsets of the population.
Results in a greater degree of representativeness by decreasing the probable sampling error.
A Stratified, Systematic Sample with a Random Start.
Cluster Sampling
A multistage sampling in which natural groups are sampled initially with the members of each selected group being subsampled afterward.
Multistage Cluster Sampling
Used when it's not possible or practical to create a list of all the elements that compose the target population.
Involves repetition of two basic steps: listing and sampling.
Highly efficient but less accurate.
Probability Proportionate to Size (PPS) Sampling
Sophisticated form of cluster sampling.
Used in many large scale survey sampling projects.
Weighting
Giving some cases more weight than others.
Probability Sampling
Most effective method for selection of study elements.
Avoids researchers biases in element selection.
Permits estimates of sampling error.
Bloom’s Taxonomy
Chapter 7
The Logic Of Sampling
Chapter Outline
Introduction
A Brief History of Sampling
Nonprobability Sampling
The Theory and Logic of Probability Sampling
Chapter Outline
Populations and Sampling Frames
Types of Sampling Designs
Multistage Cluster Sampling
Probability Sampling in Review
Political Polls and Survey Sampling
In the 2004 Presidential election, pollsters generally agreed that the election was “too close to call”.
To gather this information, they interviewed fewer than 2,000 people.
Election Eve Polls - U.S. Presidential Candidates, 2004
Election Eve Polls - U.S. Presidential Candidates, 2004
Election Eve Polls - U.S. Presidential Candidates, 2004
Bush Approval: Raw Poll Data
Observation and Sampling
Polls and other forms of social research rest on observations.
The task of researchers is to select the key aspects to observe (sample).
Generalizing from a sample to a larger population is called probability sampling and involves random selection.
Nonprobability Sampling
Technique in which samples are selected in a way that is not suggested by probability theory.
Examples include reliance on available subjects as well as purposive (judgmental), quota, and snowball sampling.
Types of Nonprobability Sampling
Reliance on available subjects:
Only justified if less risky sampling methods are not possible.
Researchers must exercise caution in generalizing from their data when this method is used.
Types of Nonprobability Sampling
Purposive or judgmental sampling
Selecting a sample based on knowledge of a population, its elements, and the purpose of the study.
Used when field researchers are interested in studying cases that don’t fit into regular patterns of attitudes and behaviors
Types of Nonprobability Sampling
Snowball sampling
Appropriate when members of a population are difficult to locate.
Researcher collects data on members of the target population she can locate, then asks them to help locate other members of that population.
Types of Nonprobability Sampling
Quota sampling
Begin with a matrix of the population.
Data is collected from people with the characteristics of a given cell.
Each group is assigned a weight appropriate to their portion of the population.
Data should represent the total population.
Informant
Someone who is well versed in the social phenomenon that you wish to study and who is willing to tell you what he or she knows about it.
Probability Sampling
Used when researchers want precise, statistical descriptions of large populations.
A sample of individuals from a population must contain the same variations that exist in the population.
Populations and Sampling Frames
Findings based on a sample represent the aggregation of elements that compose the sampling frame.
Sampling frames do not always include all the elements their names imply.
All elements must have equal representation in the frame.
A Population of 100 Folks
Sampling aims to reflect the characteristics and dynamics of large populations.
Let’s assume our total population only has 100 members.
Sample of Convenience: Easy but Not Representative
Types of Sampling Designs
Simple random sampling (SRS)
Systematic sampling
Stratified sampling
Representativeness
Representativeness - Quality of a sample having the same distribution of characteristics as the population from which it was selected.
EPSEM - Equal probability of selection method. A sample design in which each member of a population has the same chance of being selected into the sample.
Population
The theoretically specified aggregation of study elements.
Study population - Aggregation of elements from which the sample is actually selected.
Element - Unit about which information is collected and that provides the basis of analysis.
Random selection
Each element has an equal chance of selection independent of any other event in the selection process.
Sampling unit
Element or set of elements considered for selection in some stage of sampling.
Parameter
Summary description of a given variable in a population.
Practical Exercise!
Break out the M & M’s.
Brown 13%
Yellow 14%
Red 13%
Blue 24%
Orange 20%
Green 16%
Total 100%
A Population of 10 People with $0–$9
The Sampling Distribution of Samples of 1
In this example, the mean amount of money these people have is $4.50 ($45/10).
If we picked 10 different samples of 1 person each, our “estimates” of the mean would range all across the board.
Range of Possible Sample Study Results
Shifting to a more realistic example, let’s assume that we want to sample student attitudes concerning a proposed conduct code.
Let’s assume 50% of the student body approves and 50% disapproves - though the researcher doesn’t know that.
Results Produced by Three Hypothetical Studies
Assuming a large student body, let’s suppose we selected three different samples, each of substantial size.
We would not expect those samples to perfectly reflect attitudes in the whole student body, but they should come close.
Statistic
Summary description of a variable in a sample.
Sampling Error
The degree of error to be expected of a given sample design.
Confidence Level
The estimated probability that a population parameter lies within a given confidence interval.
Thus, we might be 95% confident that between 35 and 45% of all voters favor Candidate A.
Confidence interval - The range of values within which a population parameter is estimated to lie.
Sampling Frame
That list or quasi list of units composing a population from which a sample is selected.
If the sample is to be representative of the population, it is essential that the sampling frame include all (or nearly all) members of the population.
The Sampling Distribution
If we were to select a large number of good samples, we would expect them to cluster around the true value (50%), but given enough such samples, a few would fall far from the mark.
Review of Populations and Sampling Frames: Guidelines
Findings based on a sample represent only the aggregation of elements that compose the sampling frame.
Sampling frames do not include all the elements their names might imply. Omissions are inevitable.
To be generalized, all elements must have equal representation in the frame.
Simple Random Sampling
Feasible only with the simplest sampling frame.
Not the most accurate method available.
Systematic Sampling
Slightly more accurate than simple random sampling.
Arrangement of elements in the list can result in a biased sample.
Sampling ratio
Proportion of elements in the population that are selected.
Stratification
Grouping of units composing a population into homogenous groups before sampling.
This procedure, which may be used in conjunction with simple random, systematic, or cluster sampling, improves the representativeness of a sample, at least in terms of the stratification variables.
Stratified Sampling
Rather than selecting sample for population at large, researcher draws from homogenous subsets of the population.
Results in a greater degree of representativeness by decreasing the probable sampling error.
A Stratified, Systematic Sample with a Random Start.
Cluster Sampling
A multistage sampling in which natural groups are sampled initially with the members of each selected group being subsampled afterward.
Multistage Cluster Sampling
Used when it's not possible or practical to create a list of all the elements that compose the target population.
Involves repetition of two basic steps: listing and sampling.
Highly efficient but less accurate.
Probability Proportionate to Size (PPS) Sampling
Sophisticated form of cluster sampling.
Used in many large scale survey sampling projects.
Weighting
Giving some cases more weight than others.
Probability Sampling
Most effective method for selection of study elements.
Avoids researchers biases in element selection.
Permits estimates of sampling error.
Part Three
Modes of Observation
Chapter 8
Experiments
Chapter Outline
Introduction
Topics Appropriate to Experiments
The Classical Experiment
Selecting Subjects
Chapter Outline
Variations on Experimental Designs
An Illustration of Experimentation
Alternate Experimental Settings
Strengths and Weaknesses of the Experimental Method
Topics Appropriate to Experiments
Projects with limited and well-defined concepts.
Projects that are exploratory rather than descriptive.
Studies of small group interaction.
Components of Experiments
Three Pairs
Independent and dependent variables
Pretesting and posttesting
Experimental and control groups
Question
In the simplest experimental design, subjects are measured in terms of a _________ variable exposed to an _________ variable.
pretested; posttested
fluid; static
independent; dependent
dependent; independent
Answer: D
In the simplest experimental design, subjects are measured in terms of a dependent variable exposed to an independent variable.
Subjects
Experimental group - A group of subjects to whom an experimental stimulus is administered.
Control group - A group of subjects to whom no experimental stimulus is administered and who resemble the experimental group in all other respects.
Double-blind Experiment
An experimental design in which neither the subjects nor the experimenters know which is the experimental group and which is the control.
Experimental and
Control Groups
Must be as similar as possible.
Control group represents what the experimental group would have been like had it not been exposed to the stimulus.
Question
_____________ groups are groups of subjects to whom an experimental stimulus is administered.
control
experimental
purposive
triad
Answer: B
Experimental groups are groups of subjects to whom an experimental stimulus is administered.
Diagram of Basic Experimental Design
Selecting Subjects
Probability sampling
Randomization
Matching
Randomization and Matching
May not know which variables will be relevant for matching process.
Most statistics used to analyze results assume randomization.
Randomization only makes sense if you have a large pool of subjects.
Question
______________ is a technique for assigning experimental subjects to experimental and control groups randomly.
nonprobability analyses
matching
randomization
none of these choices
Answer: C
Randomization is a technique for assigning experimental subjects to experimental and control groups randomly.
Open Matrix Illustration
Preexperimental Research Designs
One-shot case study - single group of subjects is measured on a variable following experimental stimulus.
One-group pretest-posttest design - adds a pre-test for the group, but lacks a control group.
Static-group comparison - includes experimental and control group, but no pre-test.
One-Shot Case Study
A man who exercises is observed to be in trim shape.
One-Group Pretest-Posttest Design
An overweight man who exercises is later observed to be in trim shape
Static-Group Comparison
A man who exercises is observed to be in trim shape while one who doesn’t is observed to be overweight.
Question
In a one-group pretest-posttest design, what is lacking?
EPSEM
an experimental group
a control group
none of these choices
Answer: C
In a one-group pretest-posttest design, a control group is lacking.
Sources of Internal Invalidity
Historical events may occur during the course of the experiment.
Maturation of the subjects.
Testing and retesting can influence behavior.
Instrumentation
Sources of Internal Invalidity
Statistical regression of subjects starting out in extreme positions.
Selection biases.
Experimental mortality - subjects drop out of the study before it's completed.
Demoralized control group subjects.
Limiting External Invalidity
Solomon four-group design
Posttest-only control group design
The Classical Experiment
Solomon Four-group Design
Four groups of subjects, assigned randomly:
Groups 1 and 2 are the control and experimental group.
Group 3 does not have the pre-test.
Group 4 is only posttested.
Solomon Four-group Design
Solomon Four-group Design
Expected Findings
In Group 1, posttest prejudice should be less than pretest prejudice.
In Group 2, prejudice should be the same in the pretest and the posttest.
The Group 1 posttest should show less prejudice than the Group 2 posttest does.
The Group 3 posttest should show less prejudice than the Group 4 posttest does.
Question
What is the basic difference between the classical design and the Solomon four-group design?
There is no difference.
The Solomon four-group design repeats the classical design but adds groups that are not pretested.
The Solomon four-group design repeats the classical design but adds groups that are not posttested.
Answer: B
The basic difference between the classical design and the Solomon four-group design is that the Solomon four-group design repeats the classical design but adds groups that are not pretested.
Posttest-only Control Group Design
Includes Groups 3 and 4 of the Solomon design.
With proper randomization, only these groups are needed to control problems of internal invalidity and the interaction between testing and stimulus.
"Natural" Experiments
Important social scientific experiments occur outside controlled settings and in the course of normal social events.
Raise validity issues because researcher must take things as they occur.
Web-based Experiments
Increasingly, researchers are using the World Wide Web to conduct experiments.
Because representative samples are not essential in most experiments, researchers use volunteers who respond to invitations online.
Experimental Method
Strengths:
Isolation of the experimental variable over time.
Experiments can be replicated several times using different groups of subjects.
Experimental Method
Weaknesses:
Artificiality of laboratory setting.
Social processes that occur in a lab might not occur in a more natural social setting.
Quick Quiz
1. Experiments are especially well suited for research projects involving:
limited concepts
well-defined concepts
hypothesis testing
all of these choices
Answer: D
Experiments are especially well suited for research projects involving limited concepts, well-defined concepts and hypothesis testing.
2. A ____________experiment eliminates the possibility of a researcher prejudging results.
snowball
double-blind
purposive
regressive
Answer: B
A double-blind experiment eliminates the possibility of a researcher prejudging results.
3. ______________refers to the possibility that the conclusion drawn from experimental results may not accurately reflect what has gone on in the experiment itself.
exclusion
internal validity
external validity
representativeness
none of these choices
Answer: B
Internal validity refers to the possibility that the conclusion drawn from experimental results may not accurately reflect what has gone on in the experiment itself.
4. Natural experiments are most likely to resemble which one of the following designs?
static-group comparison
classical
Solomon four-group
one-group pretest-posttest
posttest-only control group design
Answer: A
Natural experiments are most likely to resemble static-group comparison designs.
5. Which of the following is the chief advantage of a controlled experiment?
they require little time
they require little money
they are artificial
the isolation of the experimental variable’s impact over time
none of these choices
Answer: D
The isolation of the experimental variable’s impact over time is the chief advantage of a controlled experiment.
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