Midterm Study Guide
Midterm Study Guide Soc 3163
Arkansas Tech University
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This 18 page Study Guide was uploaded by Krista Lindenberg on Friday February 19, 2016. The Study Guide belongs to Soc 3163 at Arkansas Tech University taught by Dr. Mikels-Schlutterman in Spring 2016. Since its upload, it has received 50 views. For similar materials see Intro to Sociological Research in Sociology at Arkansas Tech University.
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Date Created: 02/19/16
CHAPTER 1: HUMAN INQUIRY AND SCIENCE o Page 3: Looking For Reality Much of what we know, we know by agreement rather than by experience. Scientist accept an agreement reality but have special standards for doing so. Agreement reality: those things we “know” as part and parcel of the culture we share with those around us. In general an assertion must have both logical and empirical support. Epistemology is the science of knowing; systems of knowledge Methodology: The science of finding out; procedures for scientific investigation (a subfield of epistemology) o Page 17: Purposes Of Social Research Sometimes social research is a vehicle for exploring something – mapping out a topic that may warrant further study later. Some social research is done for the purpose of describing the state of social affairs. Often, social research aims at explaining something – providing reasons for phenomenon in terms of causal relationships. o Page 24: Quantitative And Qualitative Data The distinction between quantitative and qualitative data in social research is essentially the distinction between numerical and nonnumerical data. When we say someone is intelligent, we have made a qualitative claim. When psychologists and others measure intelligence through IQ scores, they are trying to quantify such a qualitative statement. Every observation is qualitative at the outset. Converting quantitative data to a numerical form can be useful at times. Quantification often makes our observations more explicit. It can also make aggregating and summarizing data easier and opens up the possibility of statically analyses. CHAPTER 2: PARADIGMS, THEORY, AND RESEARCH o Page 32: Some Social Science Paradigms There is usually more than one way to make sense of things. A paradigm is a fundamental model or scheme that organizes our view of something. Social scientists use a variety of paradigms to organize how they understand and inquire into social life. A distinction between types of theories that cuts across paradigms is macrotheory (theories about largescale features of society) versus microtheory (theories about smaller units or features of society.) Macrotheory: a theory aimed at understanding the “big picture” of institutions, whole societies, and the interactions among societies. Karl Marx’s examination of the class struggle is an example of macrotheory. Microtheory: a theory aimed at understanding social life at the level of individuals and their interactions. Explaining how the play behavior of girls differs from that of boys is an example of microtheory. o Page 55: The Links Between Theory And Research In the deductive model, research is used to test theories. In the inductive model, theories are developed from the analysis of research data. There is no simple recipe for conducting social research. It is far more openended than the traditional view of science suggests. Science depends on two categories of activity: logic and observation. In practice, there are many possible links between theory and research and many ways of going about social inquiry. Using theories to understand how society works is key to offering practical solutions to society’s problems. o Page 56: The Importance Of Theory In The “Real World” No matter what a researcher’s aims are in conducting social research, a theoretical understanding of their subject may spell the difference between success and failure. If one wants to change society, one needs to understand the logic of how it operates. “Theory helps create questions, shapes our research designs, helps us anticipate outcomes, helps us design interventions.” – William White (1997) CHAPTER 4: RESEARCH DESIGN o Page 93: Introduction Any research design requires researchers to specify as clearly as possible what they want to find out then determine the best way to do it. o Page 94: Three Purposes Of Research Exploration, Description, and Explanation. Exploration is the attempt to develop an initial, rough understanding of some phenomenon Exploratory studies are most typically done for three purposes: (1) to satisfy the researcher’s curiosity and desire for better understanding, (2) to test the feasibility of undertaking a more extensive study, and (3) to develop the methods to be employed in any subsequent study The chief shortcoming of exploratory studies is that they seldom provide satisfactory answers to research questions, although they can hint at the answers an can suggest which research me6thods could provide definitive answers. Description is the precise measurement and reporting of the characteristics of some population or phenomenon under study Because scientific observation is often careful and deliberate, scientific descriptions are typically more accurate and precise than are casual ones. Many qualitative studies aim primarily at description. Descriptive studies answer questions of what, where, when, Explanation is the discovery and reporting of relationships among different aspects of the phenomenon under study. Description studies answer the question “What so?” ; explanatory ones tend to answer the question “Why?” Explanatory studies address questions of why. o Page 97: The Logic Of Nomothetic Causality Both idiographic and nomothetic models of explanation rest on the idea of causation. The idiographic model aims at a complete understanding of a particular phenomenon, using all relevant causal factors. The nomothetic model aims at a general understanding – not necessarily complete – of a class of phenomena, using a small number of relevant causal factors. There are three basic criteria for establishing causation to nomothetic analyses: (1) the variables must be empirically associated, or correlated; (2) the causal variable must occur earlier in time than the variable it is said to affect; and (3) the observed effect cannot be explained as the effect of a different variable In other words: (1) the variables must be correlated, (2) the cause takes place before the effect, and (3) the variables are nonspurious. Correlation o Unless some actual relationship where changes in one variable are associated with changes in the other – a statistical correlation – is found between two variables, we can’t say that a causal relationship exists. o Page 109: The Time Dimension The research of social processes that occur over time presents challenges that can be addressed through crosssectional studies or longitudinal studies Crosssectional studies are based on observations made at one time. Although conclusions drawn from such studies are limited by this characteristic, researchers an sometimes use such studies to make inferences abut processes that occur over time. In longitudinal studies, observations are made at many times. Such observations may be made of samples drawn from general populations (trend studies), samples drawn from more specific subpopulations (cohort studies), or the same sample of people each time (panel studies). CHAPTER 5: CONCEPTUALIZATION, OPERATIONALIZATION, AND MEASUREMENT o Page 128: Introduction The interrelated processes of conceptualization, operationalization, and measurement allow researchers to move from a general idea about what they want to study to effective and welldefined measurements in the real world. o Page 133: Indicators And Dimensions Conceptualization gives definite meaning to a concept by specifying one or more indicators of what we have in mind. An indicator is a sign of the presence or absence of the concept we’re studying. Indicator: an observation that we choose to consider as a reflection of a variable we wish to study. For example, attending religious services might be considered an example of religiosity. Dimension: a specifiable aspect of a concept. “Religiosity” might be specified in terms of a belief dimension, a ritual dimension, a devotional dimension, a knowledge dimension, and so forth. o Page 144: Levels Of Measurement Nominal measure: A variable whose attributes have only the characteristics of exhaustiveness and mutual exclusiveness. In other words, a level of measurement describing a variable that has attributes that are merely different, as distinguished from ordinal, interval, or ratio measures. Gender is an example of a nominal measure. Nominal measures merely offer names or labels for characteristics. Ordinal measure: A level of measurement describing a variable with attributes we can rank order along some dimension. An example is socioeconomic status as composed of the attributes high, medium, low. Interval measure: A level of measurement describing a variable whose attributes are rank ordered and have equal distances between adjacent attributes. The Fahrenheit temperature scale is an example of this, because the distance between 17 and 18 is the same as that between 89 and 90. Ratio measure: A level of measurement describing a variable with attributes that have all the qualities of nominal, ordinal, and interval measures and in addition are based on a “true zero” point. Age is an example of a ratio measure. o Page 151: Criteria Of Measurement Quality Criteria of the quality of measures include precision, accuracy, reliability, and validity. Whereas reliability means getting consistent results from the same measure, validity refers to getting results that accurately reflect the concept being measured. Researchers can test or improve the reliability of measures through the testretest method, the splithalf method, the use of established measures, and the examination of work performed by researcher workers. The yardsticks for assessing a measure’s validity include face validity, construct validity, and content validity. CHAPTER 6: INDEXES, SCALES, AND TYPOLOGIES o Page 163: Introduction Single indicators of variables seldom capture all the dimensions of a concept, have sufficient validity to warrant their use, or permit the desired range of variation to allow ordinal rankings. Composite measures, such as scales and indexes, solve these problems by including several indicators of a variable in one summary measure. o Page 166: Index Construction Index: a type of composite measure that summarizes and rankorders several specific observations and represents some moregeneral dimension There are four main steps in the construction of an index: selecting possible items, examining their empirical relationships, scoring the index, and validating it. Item selection: The first step in creating an index is selecting items for a composite index, which is created to measure some variable. o Face validity: the first criterion for selecting items to be included in an index o Unidimensionality: a composite measure should represent only one dimension of a concept o General or specific: Although measures should tap the same dimension, the general dimension you’re attempting to measure may have nuances. o Variance: select items differing in variance. Examination of Empirical Relationships: The second step in index construction is to examine the empirical relationships among the items being considered for inclusion. An empirical relationship is established when respondents answer to one question help us predict how they will answer other questions. o Bivariate relationships among items: a bivariate relationship is, simply put, a relationship between two variables. o Multivariate relationships among items: more than two variables Index Scoring o When you’ve chosen the best items for the index, you next assign scores for particular responses, thereby creating a single composite index out of the several items. o First decide the desirable range of the index scores. o Second decide whether to give each item in the index equal weight or different weights. Equal weighting should be the norm. Index Validation o Item analysis: an assessment of whether each of the items is included in a composite measure makes an independent contribution or merely duplicates the contribution of other items in the measure o External Validation: the process of te4sting the validity of a measure, such as an index or scale, by examining its relationship to other presumed indictors of the same variable. If the index really measures prejudice, example, it should correlate with other indicators of prejudice. o Page 185: Likert Scaling A type of composite measure developed by Rensis Likert in an attempt to improve the levels of measurement in social research through the use of standardized response categories in survey questionnaires to determine the relative intensity of different items. Likert items are those using such responses as “strongly agree,” “agree,” “disagree,” and “strongly disagree.” o Page 190: Typologies Typology: the classification (typically nominal) of observations in terms of their attributes on two or more variables. The classification of newspapers as liberalurban, conservativeurban, or conservativerural would be an example. We attempt to assign index or scale scores to cases in such a way as to indicate a rising degree of prejudice, religiosity, conservatism, and so forth. In such cases, we’re dealing with single dimensions. Often, however, the researcher wishes to summarize the intersection of two or more variables, thereby creating a set of categories or types, which we call a typology. Typologies can be used effectively as independent variables, but interpretation is difficult when they are used as dependent variables. Chapter 1 vocabulary words Agreement Reality - Those things we 'know' as part and parcel of the culture we share with those around us Epistemology - The science of knowing; systems of knowledge Methodology - The science of finding out; procedures for scientific investigation Idiographic - An approach to explanation in which we seek to exhaust the idiosyncratic causes of a particular condition or event. Tolerance for ambiguity - the ability to hold conflicting ideas in your mind simultaneously, without denying or dismissing any of them. Chapter 2 vocabulary words Theory - systematic set of interrelated statements intended to explain some aspect of social life. Statements connected with the 'because' answers the why question. Hypothesis - a specified testable expectation about empirical reality that follows from a more general proposition, more generally, an expectation about the nature of things derived from a theory. Chapter 3 vocabulary words Indicator - An observation that we choose to consider as a reflection of a variable we wish to study. Chapter 4 vocabulary words Correlation - an empirical relationship between two variables such as 1: Changes in one or are associated with changes in the other 2: Particular attributes of one variable are associated with particular attributes of the other. Spurious Relationship - A coincidental statistical correlation between two variables shown to be caused by some third variable. Chapter 5 vocabulary words Dimension - A specifiable aspect of a concept. Nominal measure - A variable whose attributes have only he characteristics of exhaustiveness and mutual exclusiveness. In other words, a level of measurement describing a variable that has attributes that are merely different. As distinguished from ordinal interval or ratio measures. (EX gender) Ordinal Measure - A level of measurement describing a variable with attributes we can rank - order along some dimension. Interval measures - A level of measurement describing a variable whose attributes are rank ordered and have equal distances between adjacent attributes. Ratio Measure - A level of measurement describing a variable with attributes that have all the qualities of nominal. Chapter 6 vocabulary words Index - A type of composite measure that summarizes and rank orders several specific observations and represents some more general dimension Scale - A type of composite measure composed of several items that have logical or empirical structure among them. Likert Scale - a type of composite measure developed by Rensis Likert in an attempt to improve the levels of measurement in social research through the use of standardized response categories in survey questionnaires to determine the relative intensity of different items. Typology - the classification (typically nominal) of observation in terms of their attributes on two or more variables. Ex: Classification of newspapers as liberal - urban, liberal - rural, conservative - urban or conservative - rural Lecture Notes Chapter 1 Importance of research methods o Alternatives to social research Authority Tradition Common sense Media distortion Personal experience o Debunks myths: distinguish difference in what you think you know vs what you scientifically know o Science is a human made social institution and a way to produce knowledge… Useful, helpful, beneficial to understanding o Data: the empirical evidence or information that one gathers carefully according to rules or procedures Quantitative – expressed as numbers Qualitative – expressed as words, visual images, sounds, or objects o Empirical Evidence – observations that we experience through the senses o Scientific community – collection of people who practice science and a set of norms, behaviors, and attitudes that bind them together Why are research methods important? o Systematic (scientific) methods aid us in: Debunking myths Getting past our preconceived idea Enabling us to use our sociological imagination o Look at individual actions and see how structures in society and linked. Use socio imagination to stretch your thinking and make the connections. o In order to improve society o To satisfy our curiosities o In order to better understand all of the research that surrounds us every day Types of Publications o Conference presentations o Academic journals o Books – edited and nonedited o Research monograph – book length research article Academic Journals o Not for profit – subsidized by universities and professional organizations Editors and peerreviewers participate in order to establish tenure and stay abreast of current research Publishers of journals change subscriptions to universities and individuals Forms of Articles o Present new or original research o Critique existing research o Evaluate a program/policy o Review of the literature o Book reviews Chapter 2 Types of Sociological Questions Factual (what is childhood obesity) Historical (when did childhood obesity become a problem) Comparative (compare childhood obesity in races, socioeconomic groups) Theoretical (why???) Theory “…systematic set of interrelated statements intended to explain some aspect of social life” Example: “Economic distress among the white population caused an increase in mob violence against African Americans” Proposing how two things are interrelated Theory is a general proposition Hypothesis is a specified, testable, expectation Theory = two statements linked with a because Childhood obesity is more a problem in low income families because they are less likely to be able to afford healthy food. Hypothesis – a specified testable expectation about empirical reality that follows from a more general proposition Research influences policy making Three Functions of Theory 1. Theories prevent our being taken in by flukes Don’t depend on chance 2. Theories make sense of observed patterns in ways that can suggest other possibilities If we have a theory about how two things are related, we can find solutions Ex. Broken homes produce more juvenile delinquency than intact homes because of a lack of adult supervision After school youth programs Financial aid to single parents so that they can work less and spend more time with their children 3. Theories can direct research efforts, pointing toward likely discoveries through empirical observation As a social researcher… Work within one of these perspectives… Seek to extend it, challenge it, or specify it. Test alternative implications of the different perspectives against each other Example (Parenting) 1. Compartmentalization 2. Spillover Hypothesis 3. Compensatory Theory Seek to contribute something new Six important functions of lit review 1. Narrow or broaden a topic 2. Inform about the “state of knowledge” on a topic 3. To see patterns and gaps in literature 4. Stimulate creativity an curiosity 5. Provide examples 6. Enables you to better group elements that go into conducting research Methods: What you should be doing 1. Create list of concepts you plan to measure Define each concept Indicate which concepts are your independent variables and which are your dependent variables 2. Create a list of indicators you plan to use Write the questions/statements Write the response ranges Explicitly state how you plan to measure each concept For each concept determine its level of measurement (NOIR) Always ask yourself two questions!!! What do they mean and how do they measure it? What is meant by the concept? Conceptualization issue How is the concept measured? Measurement issue aka Operationalization Issue Conceptualization Concept – a mental image that summarizes a set of similar observations, feelings, or ideas… to make a concept useful it must be defined Conceptualization – process of specifying what we mean… coming up with a definition…produces an agreed upon meaning for a concept for purposes of research Must clearly specify what we mean Here is what I mean by this concept Indicator – a sign of the presence or absence of the concept being studied Dimension – a specifiable aspect of a concept Conceptualization in practice Must turn to social theory and prior research to review appropriate definitions Building knowledge; do research and literature review so that we may “stand on the shoulders of giants Newton May need to distinguish sub concepts, or dimensions, of the concept Should understand how the definition we choose fits within the research and Should understand what assumptions underlie this framework Measurement Issue Operationalization – process of connection concepts to observations When we conceptualize, we specify what we mean by a term When we operationalize, we identify specific observations that we will take to indicate that concept in empirical reality. Options for Operationalizing Concept Constructing questions Making observations Using available data Combining measurement operations 1. Constructing questions Close-ended (five choice) question – Respondents are offered explicit responses from which to choose. i. Advantages: o useful large sample, want to run statistics o Answer the question that researcher really wants them to answer o More response choices reduces ambiguity and makes it easier for respondent to answer, but only a certain amount is necessary o You know they will answer the question the way you want them to ii. Negatives: o Can obscure what people really think if the choices do not match the range of possible responses to the question o Can only be used to get at certain kinds of information Open ended questions – questions without explicit response choices; write in their own answer or verbal response i. Advantages o Useful when range of responses cannot adequately be anticipated o Useful to explore the meaning respondents give to abstract concepts ii. Negatives: o Sometimes the responses are difficult to compile and categorize… usually performed by a team 2. Making Observations Observations of characteristics of individuals, events, and places 3. Using Available Data (what we are doing) Readily accessible sources of social science data: i. Government reports ii. Law enforcement (union crime report) iii. Archives of social science surveys all hail the internet! Unlimited information available through a few simple clicks! Does the data set have the information you need to operationalize your variable? i. Avoid poorly constructed questions Have others used these indicators to measure this concept? How? i. Huge advantage ii. ICPSR: find and analyze data 4. Combining Measurement Operations Triangulation: the use of 2 or more different measures of the same variable i. Not the strangulation of a triangle, don’t worry. ii. Strengthens measurement: similar results with different measures of the same variable = evidence of validity Levels of measurement Nominal Ordinal Interval Ratio Why important? Better understand how cases vary on that variable and understand more fully what we have measured Has important implications for the type of statistics than can be used. Nominal Level of measurement Examples: nationality, occupation, or religious affiliation A, B, C, D Categorical or qualitative Can: distinguish difference Cannot: say one is “greater” than another, add, subtract, multiple, or divide Go ahead, try multiplying a nun and a monk and then subtracting them by a Baptist, let’s see what you get. They vary in quality but not in amount Special case of Dichotomies Dichotomies – variables having only 2 values i.e., gender (M or F) The level of measurement is nominal, but when a statistical procedure requires that variables be quantitative, a dichotomy can work Female (1), Not Female (0) Presence and absence of Greater and less than At the Quantitative Level Ordinal, interval, ratio Ordinal Level of measurement Examples: social class, level of conservatism, level of prejudice Underclass (1), working class (2), middle class (3), upper class (4) Not very important (1), fairly important (2), very important (3), most important (4) The numbers assigned to cases specify only the ORDER of the cases Can: distinguish difference, make greater and less than distinctions Cannot: add, subtract, multiply, or divide Index: a series of ordinal level measures may be combined into an index to assess a concept. For example: supportive parenting Interval Level of measurement Example: temperature (Fahrenheit) the numbers represent fixed measurement units but have no absolute, or fixed, zero point Can: distinguish difference, make greater and less than distinctions, add, and subtract Cannot: multiply or divide There are few true interval-level measures in the social sciences but we treat indexes as interval-level measurements Ratio Level of measurement Example: people’s income The numbers indicating the values of a variable represent fixed measuring units and an absolute zero point (Zero point means absolutely no amount of whatever the variable indicates) Only level of measurement where the amount of space between each variable is fixed. Can: distinguish difference, be added and subtracted, make greater and less than distinctions, and because the numbers begin at an absolute zero point, they can be multiplied and divided. It is usually a good idea to try to measure variables at the highest level of measurement possible… The higher the level of measurement: The more info available, The more ways we have to compare cases And the more possibilities we have for statistical analyses Criteria for measurement quality Validity and Reliability Measurement Validity Extent to which an empirical measure adequately reflects the real meaning of the concept “… a valid measure of a concept is one that is closely related to other apparently valid measures of the concept, and to the known or supposed correlates of that concept, but that is not related to measures of unrelated concepts. Four Types (actually more) of Validity Face Validity Confidence gained from careful inspection of a concept to see if it is appropriate on its face Content Validity Does the measure cover the full range of the concept’s meaning? How is it achieved? Reviewing the literature thoroughly. Criterion Validity AKA Predictive Validity Comparing scores with those from a more direct or already validated measure Ex. A measure of blood-alcohol concentration could validate a self- report measurement of drinking Ex. A measure of attendance to religious services could validate a self-report measurement of religiosity. Construct Validity The degree to which a measure relates to other variables as expected theoretically Marital satisfaction and martial fidelity Measurement Reliability Is a matter of whether a particular technique, applied repeatedly to the same object, yields the same result each time Should produce consistent results Reliability is a prerequisite for measurement validity Four Possible Indicators of unreliability Test-Rest Reliability The degree to which two measurements of a phenomenon taken at two points in time are related to each other Interitem Reliability The questions should be highly associated with each other Cronbach’s alpha is a reliability measure commonly used to measure Interitem reliability Alternate Forms (split-half method) Reliability Reverses the order of the response choices in an index or modify the question wording in minor ways and re-administer that index to subjects. If the two sets of responses are not different, then alternate- forms reliability is established. Interobserver Reliability Midterm 50 Multiple Choice Questions Chapters 1, 2, 4, 5, 6 from Babbie textbook 20 questions from lectures (I have lecture notes posted) 30 questions from book ( I have a study guide covering these) She likes lists and application questions, as well as definition questions.
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