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Exam 1 Notes.docx

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Michigan State University
SOC 282

1/8/14 Chapter 1: the What and the Why of Statistics • The research process • Asking a research question • The role of theory • Formulating the hypotheses o Independent and dependent variables: causality o Independent and dependent variables: guidelines • Collecting data o Levels of measurement o Discrete and continuous variable • Analyzing data and evaluating hypotheses o Descriptive and inferential statistics • Looking at social differences The Research Process • Theory ←→ asking the research question (examine a social relationship, study the relevant literature) → formulating the hypotheses (develop a research design) → collecting data → analyzing data → evaluating the hypotheses Asking the research question (examine a social Formulating the hypotheses → relationship, study the relevant literature) (contribute new evidence in Theory (develop a research design) literature and begin again) Evaluating the hypotheses ← Analyzing data ←Collecting data 1/13/14 Asking a research question • What is empirical research? o Research based on information that can be verified by using our direct experience o To answer research questions we cannot rely on reasoning, speculation, moral judgment, or subjective preference o Empirical:  “Are women paid less than men for the same types of work?” • The role of theory o A theory is an explanation of the relationship between two or more observable attributes of individuals or groups o Social scientists use theory to attempt to establish a link between what we observe (the data) and our understanding of why certain phenomena are related to each other is a particular way. • Formulating the hypothesis o Hypotheses:  Tentative answers to research questions (subject to empirical verification)  A statement of a relationship between characteristics that vary (variables) o Variable:  A property of people or objects that takes on two or more values  Must include categories that are both exhaustive and mutually exclusive  Examples: social class, age, gender, income • Units of analysis o The level of social life on which social scientists focus (individuals, groups, family, organizations, cities) • Types of variables o Dependent: the variable to be explained (the effect) o Independent: the variable expected to account for (the cause of) the dependent variable • Cause and effect relationships o Cause and effect relationships between variables are not easy to infer in the social sciences. Causal relationships must meet three criteria:  The cause has to precede the effect in time  There has to be an empirical relationship between the cause and effect  This relationship cannot be explained by other factors 1/14/14 Chapter 2 Frequency Distributions Outline • Frequency distributions • Proportions and percentages • Percentage distributions • Comparisons • The construction of frequency distributions o Frequency distributions for nominal variables o Frequency distributions for ordinal cariables o Frequency distributions for interval-ration variables • Cumulative distributions • Rates • Reading the research literature o Basic principles o Tables with a different format • Frequency distributions o A table reporting the number of observations falling into each category of the variable  Example: death penalty statutes • Proportions and percentages o Proportion (P): a relative frequency obtained by dividing the frequency in each category by the total number of cases o Percentage (%): a relative frequency obtained by dividing the frequency in each category by the total number of cases and multiplying by 100. o Proportions and percentages are relative frequencies • Percentage distribution • If you percentage in one direction, read the table in the other direction (percentage down, read across the table) 1/15/14 Cumulative Distributions • Sometimes we are interested n locating the relative position of a given score in a distribution • Cumulative frequency distribution: a distribution showing the frequency at or below each category (class interval or score) of the variable • Cumulative percentage distribution: a distribution showing the percentage at or below each category (class interval or score) of the variable • Rates: a number obtained by dividing the number of actual occurrences in a given time period by the number of possible occurrences • Reading statistical tables: be skeptical and critical o Basic principles for understanding what the researched is trying to tell you:  What is the source of the table?  How many variables are presented? What are their names?  What is represented by the numbers presented in the first column? In the second column? Chapter 3: Graphic Presentation • Outline o The pie chart o The bar graph o The statistical map o The histogram o Statistics in practice o The line graph o Times series charts o Distortions in graphs  It is important to choose the appropriate graphs to make statistical information coherent • Pie chart: a graph showing the differences in frequencies or percentages among categories of a nominal or an ordinal variable. The categories are displayed as segments of a circle whole pieces add up to 100 • Bar graph: a graph showing the differences • The statistical map: we can di
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