SOCA01H3 Lecture Notes - Lecture 3: Social Change
Thursday September 24, 2009 ± Lecture 3 Tables and Data and Spuriousness
Today: Read BRYM Chapter 2, UNGAR Chapter 2
From 4 photos in PPT
Variables Used Variables Ignored/inadequate
-Class -Family composition
-Race -Single family
-Ethnicity -Role
-Gender -Class
-Family -Age
-Context
Sociology VS. Journalism ± How would sociology study the 4 families?
-Use random sample to represent population.
-Measure and quantify samples
-Ex. Do systemic counting
Variables ± Take on two or more values
-Gender: Male or Female?
-Religion: What religion? How religious?
-SES: Social Economic Status
-Types on variables are:
1. Independent variable: Come first in time and cause/affect dependent variable. (Ex.
gender may affect attitude)
2. Dependent variable
*Know/ study research cycle in Brym Textbook (pg. 37), and how to read tables/graphs*
Tables and Graphs
-Need to calculate % along the independent variable
-NOTE on tables/ graphs: Number of variables, independent and dependent variables, what is the
table showing?
Methodological Issues
-Reliability: Consistency in measurement.
-Validity: Precision in measurement. (Measuring what you actually want)
-Generalizability: Access the relevance beyond case studied.
-Causality: Cause and effect relationship among variables.
*Study diagram in textbook Fig 2.3 pg. 44*
Look at Causations and Spuriousness
-Causation: Act of causing something.
-Spuriousness: False or fake.
-Causal relationships
-IV comes first in time.
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Document Summary
Thursday september 24, 2009 lecture 3 tables and data and spuriousness. Today: read brym chapter 2, ungar chapter 2. Variables take on two or more values. Types on variables are: independent variable: come first in time and cause/affect dependent variable. (ex. gender may affect attitude, dependent variable. *know/ study research cycle in brym textbook (pg. Need to calculate % along the independent variable. Validity: precision in measurement. (measuring what you actually want) Definition: being different from what it claims to be. One change in x will cause a change in y. X has correlation in y, and z is causing x and y (more powerful relationship). Sociological example: density of living condition delinquency rate. Change in divorce laws anomie suicide (social change iv) intervening dependent. Multiple variable models: series of variables that affect dv. Delinquency: failure to fulfill an obligation or commitment.
