1 / 25

URBP 204A QUANTITATIVE METHODS I Social Research Lecture I

URBP 204A QUANTITATIVE METHODS I Social Research Lecture I. Gregory Newmark San Jose State University (This lecture accords with Chapters 1,2,3,5 of Earl Babbie’s The Practice of Social Research ). How do we know anything?. Observation – our experienced knowledge “Ouch, this fire is hot!”

dore
Download Presentation

URBP 204A QUANTITATIVE METHODS I Social Research Lecture I

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. 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 Babbie’s The Practice of Social Research)

  2. 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.”

  3. 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 . . .”

  4. 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

  5. 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.”

  6. Scientific Knowledge • Logic • Theory • Observation • Data Collection • Data Analysis

  7. 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)

  8. 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

  9. 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.”

  10. A Dialectic of Data • Qualitative Data • Non-numeric information • “The adult Martian is tall!” • Quantitative Data • Numeric information • “The adult Martian is 5’8”.”

  11. 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?”

  12. 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 won’t 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. Let’s look into that!”

  13. Rational Objectivity Reconsidered • Experience is inescapably unique • Individual experience of ‘subjectivity’ • Humans seek agreement on what’s 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

  14. 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

  15. 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

  16. 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

  17. 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.”

  18. 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

  19. 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 ($)

  20. Levels of Measurement • Certain analytical techniques require certain levels of measurement • “Calculate the class’s average height (ft).” • “Calculate the class’s 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

  21. Criteria of Measurement Quality Precision (versus Accuracy) A B

  22. 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

  23. 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

  24. Reliability vs. Validity • More reliable: Quantitative, nomothetic • More valid: Qualitative, idiographic

More Related