URBP 204A QUANTITATIVE METHODS I Social Research Lecture I

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URBP 204A QUANTITATIVE METHODS ISocial Research
Lecture I

• Gregory Newmark
• San Jose State University
• (This lecture accords with Chapters 1,2,3,5 of
  Earl Babbies
• The Practice of Social Research)

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How do we know anything?

• Observation our experienced knowledge
• Ouch, this fire is hot!
• Pigeons can fly.
• Agreement our accepted knowledge
• Wait 15 minutes after eating before swimming.
• Red is a primary color.

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Errors of Casual Observation

• Inaccurate observations
• What color are my pants?
• Overgeneralization
• All women are left-handed
• Selective Observation
• This driver is slow, probably an old person
• Illogical Reasoning
• The exception that proves the rule . . .

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Guarding against those Errors

• Inaccurate observations
• Deliberate, structured measurement
• Overgeneralization
• Committing to a sufficient sample of observations
• Replicating the experiment
• Selective Observation
• Research design structures observations
• Illogical Reasoning
• Conscious use of logic
• Peer review

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Views on Reality

• Pre-Modern
• We see things as they actually are.
• Modern
• We see things subjectively, but there is an
  objective truth out there.
• Post-Modern
• We see things subjectively and that is truth.

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Scientific Knowledge

• Logic
• Theory
• Observation
• Data Collection
• Data Analysis

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What is Research?

• a process through which we attempt to achieve
  systematically and with the support of data the
  answers to a question, the resolution of a
  problem, or a greater understanding of a
  phenomenon (Leedy 1997)

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A Dialectic of Explanation

• Idiographic Explanation
• Explains a single case with excruciating detail
• Here are the 23 reasons I personally chose SJSU
  
• Specific explanation
• Nomothetic Explanation
• Explains a class of cases with economical detail
• Here are the 4 top reasons students choose SJSU
• General explanation

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A Dialectic of Theory

• Inductive Theory
• Theorizes from specific cases to general pattern
• San Jose is sunny. Oakland is sunny. LA is
  sunny. Therefore, cities in California are
  sunny.
• Deductive Theory
• Theorizes from general pattern to specific cases
• Cities in California are sunny. San Jose is in
  California. Therefore San Jose must be sunny.

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A Dialectic of Data

• Qualitative Data
• Non-numeric information
• The adult Martian is tall!
• Quantitative Data
• Numeric information
• The adult Martian is 58.

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A Dialectic of Focus

• Macrotheory
• Deals with large aggregate entities of society
• How do economic classes interact?
• Microtheory
• Deals with intimate level of individuals
• How do panhandlers and pedestrians interact?

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Theories are logical explanations

• Theories prevent our being deceived by flukes
• In theory, everyone rides the bus, so if the
  first four passengers are women, I wont assume
  that all passengers will be.
• Theories make sense of observed patterns in a way
  that can suggest other possibilities
• In theory, if we understand why people take the
  bus, we can design a policy to support that use.
• Theories shape and direct research efforts
• In theory, faster travel times encourage
  transit. Lets look into that!

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Rational Objectivity Reconsidered

• Experience is inescapably unique
• Individual experience of subjectivity
• Humans seek agreement on whats real
• Social pursuit of objectivity
• Ideas that hold up to inter-subjective scrutiny
  are considered real
• Problem Scrutiny can be skewed by culture
• E.g. Ignoring experiences of subaltern groups

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Hypothesis

• A testable expectation about empirical reality
  derived from theory
• If the theory is correct, then x will be
  observed
• Must be disconfirmable
• Examples
• Theory Crime is inversely related to income
• Hypothesis A lower income school district will
  report more crimes per capita than a higher
  income one

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Ethical Issues in Social Research

• Voluntary participation
• Deception at times research purpose concealed
• No harm to participants
• Anonymity versus confidentiality
• Institutional review boards (IRB)
• Honest analysis and reporting
• Use appropriate analytical procedures
• Disclose problems and negative results

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Moving from Theory to Research

• Conceptualization
• Specification of abstract terms in research
• Operationalization
• Development of working (operational) definitions
• Specification of procedure (operations) for
  measuring a variable
• Measurement
• Deliberate empirical observations to describe
  phenomena in terms of variable attributes

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Measurement

• Attributes
• Characteristic or quality of something
• This animal is female.
• Variables
• Logical sets of attributes
• Exhaustive every observation can be classified
• Mutually exclusive every observation classified
  once
• Female is an attribute that composes gender.

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Levels of Measurement

• Nominal Measures
• Exhaustive and mutually exclusive only
• E.g. birthplace, gender, religious affiliation
• Ordinal Measures
• Exhaustive and mutually exclusive
• Capable of being ranked in order
• E.g. social class, conservatism, level of
  satisfaction

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Levels of Measurement

• Interval Measures
• Exhaustive and mutually exclusive
• Capable of being ranked in order
• Distance separating attributes has fixed meaning
• E.g. Temperature (C or F), credit score, GRE
• Ratio Measures
• Exhaustive and mutually exclusive
• Capable of being ranked in order
• Distance separating attributes has fixed meaning
• Based on a true zero point
• E.g. Temperature (K), height (ft), income ()

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Levels of Measurement

• Certain analytical techniques require certain
  levels of measurement
• Calculate the classs average height (ft).
• Calculate the classs average birthplace.
• Measures taken at one level can be recoded into
  lower levels of measurement
• Recode heights (ft) into three ordinal
  categories.
• Recode birthplaces into three ordinal
  categories.
• Level of measurement determined by analytical
  uses you have planned
• If you are not sure how you might use the data,
  aim for the highest level of measurement

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Criteria of Measurement Quality

• Precision (versus Accuracy)
• A
  B

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Criteria of Measurement Quality

• Precision (versus Accuracy)
• Reliability
• Definition same technique yields same result
• Methods Test-retest, Split-half, pre-established
• Research workers are not always reliable
• Validity
• Definition accurately measures the concept it is
  intended to measure

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Types of Validity

• Face Validity
• Indicator seems reasonable on its face
• Grievances as a measure of worker morale
• Criterion-related Validity
• Indicator relates to some external criterion
• SAT scores as a predictor of college GPA
• Construct Validity
• Indicator relates to other variables as expected
  within a system of theoretical relationships
• Comparing marriage satisfaction to marriage
  fidelity
• Content Validity
• Indicator covers the range of meanings associated
  within a concept
• Planning licensing exam covers all the planning
  skills

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Reliability vs. Validity

• More reliable Quantitative, nomothetic
• More valid Qualitative, idiographic