SOC 383 - EXAM 1 Study

SOC 383 - EXAM 1 Study 

Readings - Ch. 1.2.4.5



  • Types of Research: 

    • Descriptive - statistics of general population

    • Exploratory - qualitative

    • Explanatory - theory

    • Evaluatory - research, impact of law, policy, etc. change



  • Scientific Method

  1. Observations 

  2. Generalizations 

  3. Reasoning

  4. Potentially re-evaluate

  • Errors/Bias 

    • Selective observation - choose to observe select few 

    • Inaccurate observations - general errors/misjudgements 

    • Over generalization - assuming true for all/larger group

    • Illogical Reasoning - jumping to conclusions

    • Resistance to change 

  • Variables

    • Independent Var: ~cause - factors that INFLUENCE

    • Dependent Var: ~effect - ARE influenced 

DV

IV

IV

IV

DV




DV




  • IV → DV ++++++ (positive correlation)

  • IV → DV --------- (negative correlation)

  • IV → ^ Mediating concept^→ DV (all or part of relationship explained by outside mediator influencing both pieces)

    • Ex: social class → gpa (mediate) → school funding/resources

  • IV → \/ Moderating concept \/ → DV (the moderator changes the outcome based on its involvement from IV to DV)

    • Ex: education → gender → wages  

  • IV X→X DV Confounder impacts both separately and they are not actually related

    • Ex: Ice Cream X→X Drowning - confounder is season

  • Types of Validity

    • Measurement validity: are we actually measuring the concepts we think we are?

      • Face validity: appears appropriate and valid on its face (layperson can understand)

      • Content Validity: fully capture concepts

      • Criterion Validity: values/measures can be compared with a more direct/already valid source of measure 

        • Ex: direct/objective (statistics) vs indirect/subjective (self-report)

        • Generalizability: are results applicable to broader pop?

      • Construct Validity: no criterion is available, showing relationship between concepts based on prior research 

    • “Generalizability of a study is the extent to which it can inform us about persons, places, or events that were not directly studied.” Ch. 1

    • Causal/Internal Validity: how confident that X→Y etc ? 

  • Deduct from theory to data - DTD

  • Induct from data to theory - IDT

  • Conceptualization

    • Concept - Mental image that summarizes a set of similar observations, feelings, or ideas

    • Conceptualization - The process of specifying what we mean by a term; Used to make sense of related observations

    • Operationalism - The process of specifying the measures that will indicate the value of cases on a variable; Connects concepts to measurement

    • Concepts → Variables → Indicators

  • Levels of Measurement

    • Nominal: Categorical, no order or ranking

    • Ordinal: Categorical with ranking 

    • Interval: Fixed value units with no meaningful zero point

    • Ratio: Fixed value units with a meaningful zero point

  • Measurement Reliability

    • Reliability is easier to test than validity

    • Multiple Times

      • Test-retest Reliability

      • Intra-rater Reliability

      • Alternate forms Reliability

    • Multiple Items Reliability

      • Inter-term Reliability

      • Split-half Reliability

    • Multiple Observers Reliability

      • Interobserver: Consistency in measurement by 2 different observers

      • Intercoder: Consistency in coding by 2 different coders

  • Sampling and Generalizability

    • Population - The entire set of individuals or other entities to which study findings are to be generalized

    • Sample - A subset of a population used to study the population as a whole

    • Elements - The individual members of the population whose characteristics are to be measured

    • Sampling Frame - list of all elements in the population to draw samples from (we often rely on to pull from) 

    • Sample Unit: units lifted from each stage of multi-stage design

    • Sample Error: your statistics of sample are different from the population

    • Samples - A subset of a population used to study the population as a whole

    • Probability sampling

      • Systematic Random Samples - A method of sampling in which sample elements are selected from a list or from sequential files, with every nth element being selected after the first element is selected randomly

      • Simple Random Samples - A method of sampling in which every sample element is selected purely on the basis of chance through a random process

      • Stratified Random Samples

        • Proportionate - Sampling method in which elements are selected from strata in exact proportion to their representation in the population

        • Disproportionate - Sampling in which elements are selected from strata in proportions different from those that appear in the population

      • Multistage Cluster Sampling - randomly selecting at each level/stage of the clusters 

        • Ex: country, state, county, town, neighborhood 

    • Non-probability sampling

      • Convenience Sampling - Sampling in which elements are selected on the basis of convenience

      • Quota Sampling - A nonprobability sampling method in which elements are selected to ensure that the sample represents certain characteristics in proportion to their prevalence in the population.

      • Purposive Sampling - A nonprobability sampling method in which elements are selected for a purpose, usually because of their unique position

      • Snowball Sampling - A method of sampling in which sample elements are selected as successive informants or interviewees identify them

  • Research Design

    • Cross-sectional: A study in which data are collected at only one point in time.

    • Longitudinal: Multiple points in time

    • Panel: Same people over time

    • Trend: Repeated cross-section of the same population over time

    • Cohort: Trend or panel

  • Units of Analysis

    • Individuals vs Groups of Individuals

    • Don’t want to generalize from higher units to lower ones and vice versa