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SOC222H5 (25)
Chapter 1

Chapter 1 - Introduction

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Department
Sociology
Course
SOC222H5
Professor
Weiguo Zhang
Semester
Fall

Description
Chapter 1: Introduction 1.1 W HY STUDY STATISTIC?  Sociology scientific in the sense that social scientists attempt to verify their ideas/theories through research  Importance of stats shown by reviewing research process as it operates in social sciences  Research: any process by which information is systematically and carefully gathered for purpose of answering questions, examining ideas, or testing theories o Statistical analysis is only relevant for those research projects where the information collected is represented by numbers  Data: numerical information  Purpose of stats- manipulate and analyze data  Statistics: set of mathematical techniques used by social scientists to organize and manipulate data for the purpose of answering questions and testing theories  Mere presence of numbers guarantees nothing about quality of scientific inquiry  Researcher must be able to use statistics effectively to organize, evaluate and analyze data 1.2 ROLE OFS TATISTICS ISCIENTIFIINQUIRY  The wheel of science: theory -> hypotheses -> observations -> empirical generalizations o Based on Walter Wallace- how knowledge base of scientific enterpirse grows/develops o Scientific theory and research continually shape each other o Stats one of the most important means by which research and theory interact o Illustrates how theory stimulates research and how research shapes theory  Theory: explanation of relationships between phenomena  Scientific theory subject to rigorous testing process  I.e. Health inequality o Materialistic theory (Douglas Black)- health affected by social class; health linked to person’s social class and access to items  Variable: any trait that can change values from case to case (i.e. gender, age, ethnicity)  Independent variables: cases  Dependent variables: effects/result variables  Hypothesis: statement about the relationship between variables that, while logically derived from the theory, is much most specific and exact  Decide exactly how data will be gathered o Leads to observation phase where we actually measure social reality  Statistics are crucial; without stats, quantitative research is not possible  Only by application of statistical techniques can mere data help us shape and refine theories  Role of statistics limited o Scientific research proceeds through several mutually interdependent stages, and stats become relevant only at the end of observation stage o Inappropriate statistical applications limit usefulness of even good data  Mostly focus on assessing theory but other patterns should also be observed in data o Develop some generalizations based on empirical patterns observed o Develop tentative explanations and begin to revise or elaborate theory  Statistics are one of the most important links between the realms of theory and research o Permit us to analyze data, identify and probe trends and relationships, develop generalizations, and revise and improve theories 1.3 DESCRIPTIVE AND INFERENTIAL STATISTICS  Two general classes of statistical techniques (depending on research situation) that can be used to manipulate data Descriptive Statistics •used in certain situations: research needs to summarize/describedistribution of a single variable (univariate) or when researcher wants to descripe the relationship between two or more variables (bivariate or multivariate) •to describe a single variable, we would arrange values/scoresof that variable so that relevant information is clearly presented •percentages, graphs and charts used to describe single variables •reducing large amount of information/datainto few easily understood numbers; called data reduction (process of allowing few numbers to summarize many number; basic goal of univariate descriptive statistical procedures) •measures of association- allow researcher to quantify strength and direction of a relationship •causation and prediction •help us trace ways in which some variables have causal influences on others; and deping on strength of relationship, they allow us to predict scores on one variable from scores on another •measures of associationcan be taken as important clues about causation, but mere existence of relationship cannot be conclusivelyproof of causation •other variables may have effect on relationship Inferential Statistics •becomesrelevant when we generalize our findings from sample to a population •population is the total co
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