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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