SOC 380 Exam 3 Study Guide
SOC 380 Exam 3 Study Guide SOC 380 001
Popular in Introduction to Research Methods
SOC 380 001
verified elite notetaker
Popular in Sociology
This 7 page Study Guide was uploaded by Maddie Butkus on Sunday April 24, 2016. The Study Guide belongs to SOC 380 001 at Ball State University taught by Dr. Rachel Kraus in Winter 2016. Since its upload, it has received 29 views. For similar materials see Introduction to Research Methods in Sociology at Ball State University.
Reviews for SOC 380 Exam 3 Study Guide
Report this Material
What is Karma?
Karma is the currency of StudySoup.
You can buy or earn more Karma at anytime and redeem it for class notes, study guides, flashcards, and more!
Date Created: 04/24/16
SOC 380 Exam 3 Study Guide Descriptive Statistics: stats used to describe the distribution of and relationship among variables Inferential Statistics: stats used to estimate how likely it is that a statistical result based on data from a random sample is representative of the population from which the sample is assumed to have been selected. Correlation coefficient: The correlation coefficient is a measure that determines the degree to which two variable's movements are associated Meaning of statistical significance: mathematical likelihood that an association is not the result of chance, judged by a criterion the analyst sets (probability is less that .05) Measures of central tendency: Mode: frequency that occurs most often Median: position average or divides the distribution in half (50 th percentile) Mean: arithmetic average; = sum of values/# of values Measures of variance: capture how widely and densely spread Range: simplest measure of variance; = highest value – lowest value +1 Variance: statistic that measure the variability of a distribution as the average squared deviation of each case from the mean. Standard deviation: distance from the mean that covers a clear majority of cases (2/3) Coding: proves of transforming raw data into a “standardized” form - Type of content analysis involving logic of conceptualization and operationalization - Coding in Content Analysis o Content analysis is essentially a coding operation Coding is the process of transforming raw data into a standardized form o Coding in content analysis involves the logic of conceptualization and operationalization. o Define set of coding categories Deductive: pre-established codes (from theory, past research, what you look for) “decision rules” to apply codes (when X occurs in data, it receives y code) applying codes to body of text: place data into codes Content analysis: - Unit of analysis: tangible “thing” we examine, want to learn about, understand, (artifact we are examining; commercial, books, movies) - Unit of observation: what we look at to understand the “thing,” path we use to get to understanding o EX: learn about a novelist (unit of analysis = individuals) by examining the novels they write (unit of observation) o EX: learn about commercials by watching commercials; Unit of analysis and unit of observation are the same thing Manifest vs. latent coding: - Manifest: right up front, noticeable. - Latent: hidden message Inter-coder reliability: Inter-coder reliability refers to the extent to which two or more independent coders agree on the coding of the content of interest with an application of the same coding scheme. In surveys, such coding is most often applied to respondents' answers to open-ended questions, but in other types of research, coding can also be used to analyze other types of written or visual content. Inter-coder reliability is a critical component in the content analysis of open-ended survey responses Archival research: written or visual records, not produced by the researcher Writing tips: -Don’t expect to write a polished draft the first time around - Leave time for revision and accept much of your writing will be discarded - Write as fast as you can and spell/grammar check later - Ask for reactions from other people you trust - Draft segments as you go; don’t write at once - Shorted and clarify statements - Make sure each paragraph only concerns 1 topic Applied research reports: The goal of research is not just to discover something, but to communicate that discovery to a larger audience. A successful report must be well organized and clearly written Tips for writing a report: o Don’t expect to write a polished draft in linear fashion o Leave time for revisions Characteristics of a good literature review: - identify gaps in current knowledge - integrated literature review should: o be directly tied to the research question o summarize prior research be selective; not just the first articles be up to date use direct quotes sparingly o Critique prior research o Inform hypotheses o Present pertinent conclusions (relevant to our study) Distinguish your opinion clearly from research conclusions Don’t emphasize problems that you can’t avoid either. Field research: (P. 206) - Complete observation: role in participant observation in which the researcher does not participate in group activities and is publicly defined as a researcher - Reactive effects: changes in an individual that result from being observed or otherwise studied. - Complete participation: role in field research in which the researcher does not reveal his or her identity as a researcher to those who are observed. - get approval to observe - must be sensitive to the impression they make and ties established when entering the field - collects data from people who have different perspectives and for developing relationships that the research can use to surmount the problems in data collection that arise in the field - researcher needs to be ready to explain to participants - Gatekeeper: a person in a field setting who can grant researchers access to the setting. - Key Informant: an insider who is willing and able to provide a field researcher with superior access and information including answers to questions that arise during the research. - Develop a plausible explanation for yourself and your study and keeping the support of key individuals to maintain relationships in the field. Participant observer: a qualitative method for gathering data that involves developing a sustained relationship with people while they go about their normal activities. Reflexivity: (P. 240) - Reflexivity entails the researcher being aware of his effect on the process and outcomes of research - Honest and informative account about how the researcher interacted with subjects in the field, what problems they encountered and how these problems were or were not resolved. Conversation analysis: (P. 243) - qualitative method for analyzing ordinary conversations. Unlike narrative analysis conversation analysis focused on the sequence and details of conversational interaction rather than on the “stories” people are telling. Like ethnomethodology, from which it developed, conversation analysis focuses on how reality is constructed rather than on what it is. - Three Premises: o Interaction is sequentially organized and talk can be analyzed in terms of the process of social interaction rather than in terms of social interactions rather than in terms of motives or social status. o Talk as a process of social interaction, is contextually oriented – it both is shaped by interaction and creates the social context of that interaction o These processes are involved in all social interaction, so no interactive details are irrelevant to understanding it Grounded theory: systematic theory developed inductively, based on observations that are summarized into conceptual categories, reevaluated in the research setting and gradually refined and linked to other conceptual categories. Ethnomethodology: qualitative research method focused on the way that participants in a social setting create and sustain a sense of reality Netnography: use of ethnographic methods to study online communities Nomothetic and idiographic explanations: Represent an understanding to social life - An idiographic method focuses on individual cases or events. Ethnographers, for example, observe the minute details of everyday life to construct an overall portrait of a specific group of people or community - A nomothetic method, on the other hand, seeks to produce general statements that account for larger social patterns, which form the context of single events, individual behaviors, and experience. Qualitative data analysis Steps in qualitative Data Analysis: 1. Documentation of the data (interview transcripts) 2. Coding 3. Examining relationships in the data to show how one concept may influence another 4. Authenticating conclusions by evaluations of alternative explanations; credibility based on data (offers questions from the data to illustrate concepts, patters of ideas) Analyzing Qualitative Data - initial or “open” coding stage: line by line coding using phrases explicitly found in the data - Codes combined into broader themes - Constant comparative method: data are constantly checked and re-checked against the broader theme o New data constant re-examined whether or not the examples really “fit” that theme of if they are demonstration something else, If not…. They are reexamined for possible new themes Themes/patterns may be discarded if found the aren’t “really” relevant Numerous readings and re-readings of data Importance of examining relationships between concepts - There are no variables or numbers; we need thick descriptions to find relationships & explanations - Examining relationships in the data to show how one concept may influence another - Authenticating conclusions by evaluating alternative explanations; credibility based on data (offers quotes from the data to illustrate concepts, patterns, or ideas.) o Use quotes to identify findings, patterns from data Interviewing and saturation: point at which subject selection is ended in intensive interviewing because new interviews seem to yield little additional information. Focus groups: A qualitative method that involves unstructured group interviews in which the focus group leader actively encourages discussion among participants on the topics of interest. Ethics involved in qualitative data ANALYSIS (P. 254) - research integrity and quality: study is conducted carefully, thoughtfully and correctly in terms of some reasonable set of standards. Produce authentic and valid conclusions. - Ownership of data and conclusions: conflicts of interest between different stakeholders much more difficult to resolve. Working though the issues as they arise is essential. - Use and misuse of results: it is prudent to develop understandings early in the project with all major stakeholders that specify what actions will be taken to encourage the appropriate use of project results and to respond to what is considered misuse of these results Criteria for assessing the quality of a research article (cannot find much information on this) - peer reviewed - methods - sample population - findings Your preferred research method: qualitative, quantitative or content analysis. It’s strengths and weaknesses (this is my own answer) Surveys: excellent for generalizable studies of large populations o Multiple variables o Allow for statistical testing of hypothesis o May be inaccurate and low on nuance, context
Are you sure you want to buy this material for
You're already Subscribed!
Looks like you've already subscribed to StudySoup, you won't need to purchase another subscription to get this material. To access this material simply click 'View Full Document'