SOC 380 Study Guide for Final Exam PDF

**[SOC 380 Study Guide for Final Exam]** **[Block 1]** Be able to define and apply the following concepts: 1. the errors of personal inquiry a. Overgeneralization: Drawing conclusions from a small sample or isolated experience. b. Selective Observation: Focusing on informatio...

**[SOC 380 Study Guide for Final Exam]** **[Block 1]** Be able to define and apply the following concepts: 1. the errors of personal inquiry a. Overgeneralization: Drawing conclusions from a small sample or isolated experience. b. Selective Observation: Focusing on information that confirms preexisting beliefs while ignoring contradictory evidence. c. Premature Closure: Stopping the inquiry process too soon, without fully exploring the topic. d. Halo Effect: Letting one positive or negative trait influence the overall judgment. 2. scientific inquiry e. Scientific inquiry refers to the systematic approach used to collect data, analyze it, and reach conclusions. In sociology, it involves using empirical research methods to test hypotheses, uncover patterns, and develop theories. It differs from personal inquiry in that it is based on structured, objective methods and logical reasoning. 3. the foundations of social science f. Empirical Observation: Collecting data based on observable phenomena. g. Theory: Developing ideas or models to explain social phenomena. h. Objectivity: Maintaining neutrality and avoiding personal biases in research. i. Systematic Study: Using a structured approach to gather and analyze data. j. Interdisciplinary Nature: Drawing from various disciplines (e.g., sociology, psychology, economics) to understand social behavior. 4. Variables k. Variables are characteristics or properties that can take on different values. In research, variables are used to examine relationships between different factors. 5. Attributes l. Attributes are specific characteristics or qualities that describe a variable. For example, if \"education level\" is a variable, attributes could include \"high school diploma,\" \"bachelor\'s degree,\" and \"graduate degree.\" 6. the four purposes of research m. Exploration: Investigating a new topic or phenomenon to gather basic information. n. Description: Providing a detailed account of the characteristics of a situation or group. o. Explanation: Understanding the causes or reasons behind a particular social phenomenon. p. Prediction: Using research to forecast future trends or behaviors based on existing data. 7. independent and dependent variables q. Independent Variable (IV): A variable that is manipulated or categorized to determine its effect on another variable. r. Dependent Variable (DV): A variable that is influenced or changed by the independent variable. Questions: - How does science compare to other systems for understanding the world? - Science uses systematic, evidence-based methods to understand the world, relying on observation and testing. In contrast, tradition follows passed-down beliefs, authority depends on expert opinion, intuition relies on gut feelings, and personal experience is subjective and anecdotal. - Compare and contrast idiographic and nomothetic methods of inquiry. - Idiographic: Focuses on understanding individual cases in detail (qualitative). - Nomothetic: Seeks general laws or patterns across large groups (quantitative). - Compare and contrast inductive and deductive reasoning. - Inductive: Starts with specific observations and builds general theories. - Deductive: Starts with a theory and tests it through specific observations. - Compare and contrast quantitative and qualitative data. - Quantitative: Numerical data used for statistical analysis (objective). - Qualitative: Descriptive data that explores experiences or behaviors (subjective). - What do we mean by the concept "data or research literacy"? - The ability to understand, interpret, and evaluate research and data effectively. It involves knowing how to assess research quality, interpret findings, and make informed decisions based on data. **[Block 2]** Be able to define and apply the following concepts: 1. Theory a. A theory is a set of ideas that explains social phenomena. It provides a framework for understanding observations. 2. Paradigms b. Paradigms are broad frameworks that shape how we interpret the world and approach research. (Application: A researcher's paradigm (e.g., structural functionalism or symbolic interactionism) determines their focus and approach to studying social issues.) 3. inductive and deductive approaches c. Inductive: Starts with observations to form generalizations. d. Deductive: Starts with a theory or hypothesis and tests it through observations 4. the five paradigms discussed in class (structural functionalism, social conflict, symbolic interactionism, etc.) e. Structural Functionalism: Views society as a system of interrelated parts that maintain stability. f. Social Conflict: Focuses on power and inequality between social groups. g. Symbolic Interactionism: Examines how individuals create meaning through interactions. h. Feminist Theory: Analyzes gender inequalities and roles in society. i. Social Constructionism: Argues that reality is created through social interactions and language. Questions: - What are the functions of theory? - Explanation: It helps explain social phenomena and relationships. - Prediction: It allows for predicting future outcomes based on existing patterns. - Understanding: It helps develop a deeper understanding of social behavior. - Guiding Research: It provides a framework for formulating hypotheses and conducting studies - Describe the traditional model of science. - Observation: Collecting data or making observations about the world. - Hypothesis: Formulating a testable prediction or explanation. - Experimentation: Testing the hypothesis through controlled methods. - Analysis: Analyzing the results to see if they support or refute the hypothesis. - Conclusion: Drawing conclusions based on the analysis and refining the theory if necessary. **[Block 3 ]** Be able to define and apply the following concepts: 1. voluntary participation a. Voluntary participation means that individuals choose to participate in research without any coercion or undue pressure. Participants have the right to withdraw at any time without consequences. 2. informed consent b. Informed consent requires that participants are fully aware of the nature of the study, including risks, benefits, and their rights, before agreeing to participate. 3. the general principles of the Belmont report c. Respect for Persons: Protecting participants\' autonomy and ensuring voluntary participation. d. Beneficence: Maximizing benefits and minimizing harm to participants. e. Justice: Ensuring fairness in selecting participants and distributing research benefits. 4. the general principles of the ASA Code of Ethics [asa\_code\_of\_ethics-june2018.pdf (asanet.org)](https://www.asanet.org/sites/default/files/asa_code_of_ethics-june2018.pdf) f. Professional and Scientific Responsibility: Researchers must conduct studies with integrity and professionalism. g. Respect for People\'s Rights, Dignity, and Diversity: Researchers must respect participants\' rights, dignity, and privacy. h. Social Responsibility: Sociologists must contribute to the public good and use their work to improve society. i. Conflicts of Interest: Researchers must avoid conflicts of interest and disclose any potential biases. j. Research Ethics: Ensuring that research is designed and conducted ethically, with participant welfare in mind. Questions: - What are the risks associated with deception? When can it be used? - Risks: - Emotional Distress: Participants may feel betrayed or upset when deception is revealed. - Loss of Trust: It may reduce trust in researchers or the scientific community. - Ethical Concerns: Deception can conflict with the principles of respect and honesty. - When It Can Be Used: - It is essential to the study's validity. - The benefits outweigh the risks. - Participants are debriefed afterward to explain the deception and address any concerns. - What are the challenges associated with articulating and enforcing a code of ethics? - Ambiguity: Ethical dilemmas often lack clear solutions, making guidelines hard to apply consistently. - Diversity: Different cultural and institutional norms may conflict with standardized ethical codes. - Enforcement: Monitoring adherence and addressing violations can be difficult due to limited oversight or unclear consequences. - Why is it so difficult to ensure anonymity to subjects? Why is anonymity desirable? Why is confidentiality at times more desirable over anonymity? - Challenges Ensuring Anonymity: Data may unintentionally reveal identities (e.g., demographic details). Longitudinal studies or linked data make anonymity harder to maintain. - Why Anonymity Is Desirable: Encourages honest responses by protecting privacy and reducing fear of identification. - Why Confidentiality May Be Preferred: Confidentiality allows researchers to collect and use identifiable data (e.g., for follow-ups) while still protecting participants from public exposure. - Compare and contrast anonymity and confidentiality - Anonymity: No identifiers are collected, making it impossible to link data to individuals. Example: Anonymous surveys with no personal details collected. - Confidentiality: Identifiers are collected but are kept private and secure. Example: A study where names are recorded but only accessible to the researcher.   **[Block 4]** Be able to define and apply the following concepts: 1. the criteria for causality a. Correlation: There must be a relationship between the variables. b. Time Order: The cause must precede the effect. c. Non-Spuriousness: The relationship cannot be explained by another variable. d. Application: Studying whether higher education levels lead to higher income requires proving the above criteria. 2. ecological fallacy e. The ecological fallacy occurs when conclusions about individuals are drawn from group-level data. f. Application: Assuming all individuals in a wealthy neighborhood are rich because the area's average income is high. 3. individualistic fallacy g. The individualistic fallacy occurs when conclusions about groups are drawn from individual-level data. h. Application: Concluding a whole school performs poorly based on one student\'s failing grades. 4. Reductionism i. Reductionism oversimplifies explanations by focusing on a single cause or level of analysis, ignoring other factors. j. Application: Explaining societal inequality solely through individual effort without considering systemic factors. 5. units of analysis (individual, group, etc.) k. The unit of analysis refers to what is being studied in a research project, such as: l. Individual: A single person (e.g., a student). m. Group: Families, teams, or communities. n. Organization: Companies or institutions. o. Social Artifact: Documents, media, or cultural objects. p. Application: A study of voting behavior at the individual level versus examining national trends 6. retrospective studies q. Retrospective studies examine past events or behaviors to understand their causes or impacts. r. Application: Interviewing adults about their childhood experiences to study the effects of early education. 7. steps of social research s. Define the Problem: Identify what you want to study. t. Review Literature: Understand existing knowledge. u. Formulate Hypotheses: Develop testable predictions. v. Choose a Method: Select qualitative, quantitative, or mixed methods. w. Collect Data: Gather information systematically. x. Analyze Data: Interpret results using appropriate tools. y. Report Findings: Share conclusions through writing or presentations. Questions: - What are the strengths and weaknesses of longitudinal research? Provide an example of a study that would benefit from a longitudinal approach. - Strengths: Tracks changes over time, revealing trends and causality. Provides richer data for understanding long-term effects. - Weaknesses: Time-consuming and costly. Participant attrition (dropout) can affect results. Maintaining consistency in data collection over time is challenging. - Example: A study examining how early childhood education impacts career success would benefit from a longitudinal approach to track participants from childhood to adulthood. - Compare and contrast units of analysis and units of observation. - Units of Analysis: The primary entity being studied (e.g., individuals, groups, organizations). Example: Studying student test scores (individuals). - Units of Observation: The source of the data collected. Example: Collecting test scores from school records. - Compare and contrast cross-sectional and longitudinal approaches. - Cross-Sectional: Data is collected at one point in time. - Strengths: Quick, less expensive, and good for identifying associations. - Weaknesses: Cannot determine causality or track changes over time. - Example: Surveying people's opinions on a political issue today. - Longitudinal: Data is collected over multiple time points. - Strengths: Tracks changes, identifies causality, and captures trends. - Weaknesses: Time-intensive and expensive. - Example: Following a group of voters over several election cycles to study shifts in political preferences. **[Block 5]**\ Be able to define and apply the following concepts: 1. Concept a. A concept is an abstract idea or construct used to represent social phenomena. b. Application: Concepts like \"social class\" or \"poverty\" provide a basis for research and analysis. 2. operational definition c. An operational definition specifies how a concept will be measured or observed in a study. d. Application: Defining \"income level\" as annual earnings reported in dollars for measuring social class. 3. Reliability e. Reliability refers to the consistency or stability of a measure across time and contexts. f. Application: A reliable survey produces the same results when repeated with similar participants under the same conditions. 4. Validity g. Validity refers to the extent to which a measure accurately represents the concept it claims to measure. h. Application: A test claiming to measure intelligence must assess cognitive ability rather than unrelated factors like test-taking skills. 5. nominal, ordinal, interval and ratio i. Nominal: Categorizes data without order. Example: Gender, race, or favorite color. j. Ordinal: Categorizes with a meaningful order but without consistent intervals. Example: Social class (low, middle, high). k. Interval: Has ordered categories with equal intervals, but no true zero point. Example: Temperature in Celsius or Fahrenheit. l. Ratio: Ordered, equal intervals, and has a true zero point. Example: Income, age, or weight. Questions: - How do researchers balance the benefits of increased reliability of variables and reduced richness of meaning? - Using Multiple Measures: Combining standardized tools for reliability with open-ended methods to capture nuanced meaning. - Prioritizing Research Goals: Choosing greater reliability for large-scale studies and richness of meaning for exploratory research. - Iterative Refinement: Testing and refining variables to achieve a balance between consistency and depth. - Compare and contrast conceptualization and operationalization. - Conceptualization: Defining the abstract meaning of a concept. Example: \"Poverty\" as a lack of resources to meet basic needs. - Operationalization: Determining how the concept will be measured. Example: Measuring \"poverty\" using income levels below a specific threshold. - Compare and contrast nominal and interval/ratio variables. - Nominal Variables: Categories with no meaningful order or numerical relationship. Example: Types of pets (dog, cat, bird). - Interval/Ratio Variables: Ordered, numerical data; interval lacks a true zero, while ratio includes one. Example: Interval: Temperature in Celsius; Ratio: Age or income. - Compare and contrast reliability and validity. - Reliability: Consistency of a measure; the extent to which it produces the same results over time or across contexts. Example: A scale consistently showing the same weight for an object. - Validity: Accuracy of a measure; the extent to which it measures what it claims to measure. Example: A scale measuring weight, not height, when assessing body mass. **[Block 6]** Be able to define and apply the following concepts: 1. Indexes a. An index is a composite measure that combines multiple indicators into a single score to represent a concept. Each indicator contributes equally to the index. b. Application: A socioeconomic status (SES) index combining income, education, and occupation scores to measure overall social standing. 2. Scales c. A scale is a composite measure that accounts for varying intensities or degrees of a concept. Different items may have different weights based on their importance or strength. d. Application: A Likert scale measuring attitudes toward climate change, where responses range from \"strongly disagree\" to \"strongly agree.\" 3. Typologies e. Typologies classify data into categories based on two or more dimensions or variables. They are used to create groups with distinct characteristics. f. Application: A typology of leadership styles combining dimensions like \"authoritarian\" vs. \"democratic\" and \"task-oriented\" vs. \"relationship-oriented.\" Questions: - What is the process a researcher would go through to create an index? A scale? - Process to Create an Index - Step 1: Select Indicators: Choose variables representing the concept (e.g., education, income for SES). - Step 2: Score Indicators: Assign values to each indicator (e.g., 1 for low income, 5 for high income). - Step 3: Combine Scores: Sum or average the indicator scores to create the index. - Step 4: Validate the Index: Test its reliability and validity by comparing it to other measures of - Process to Create a Scale - Step 1: Develop Items: Write questions or statements representing varying intensities of the concept. - Step 2: Pre-Test Items: Administer the items to assess their effectiveness in differentiating respondents. - Step 3: Weight Items: Assign scores to responses based on their intensity (e.g., \"strongly agree\" = 5, \"agree\" = 4). - Step 4: Analyze Consistency: Use statistical tools like Cronbach's alpha to ensure the items measure the concept consistently. - Step 5: Validate the Scale: Ensure the scale accurately reflects the concept being measured. - What questions should a researcher ask when deciding how to score an index? - Are all indicators equally important? If not, consider weighting them differently. - Should missing responses be excluded or imputed? Missing data may require adjustments. - Does the scoring align with the concept? Ensure the combined score meaningfully represents the concept. - What options are available to a researcher if a respondent did not answer all of the questions in a survey? - Exclude the Case: Use only respondents with complete data, which may reduce sample size. - Impute Missing Values: Estimate the missing values using statistical methods like mean imputation or regression. - Use Partial Data: Analyze the completed portions of the survey if the missing data is not crucial. - Add a "No Response" Category: Treat non-responses as a separate category when appropriate. - Compare and contrast a Likert Scale and a Semantic Differential. - Likert Scale: - Format: Respondents rate agreement/disagreement with statements on an ordinal scale (e.g., \"strongly agree\" to \"strongly disagree\"). - Purpose: Measures attitudes or opinions. - Example: "I am satisfied with my job: Strongly agree / Agree / Neutral / Disagree / Strongly disagree." - Semantic Differential: - Format: Respondents rate concepts on a bipolar scale between two opposite adjectives (e.g., \"happy\" vs. \"sad\"). - Purpose: Measures the connotations or emotional responses to concepts. - Example: "How do you feel about this product? Useful \_ \_ \_ \_ Useless." **[Block 7]** Be able to define and apply the following concepts: 1. qualitative research a. Qualitative research is a type of research that focuses on understanding phenomena through in-depth exploration of experiences, behaviors, and meanings, often using non-numerical data. b. Application: Conducting interviews or focus groups to explore the experiences of people living in poverty. 2. Ethnography c. Ethnography is a qualitative research method where researchers immerse themselves in a community or social group to understand its culture, behaviors, and social interactions. d. Application: A researcher spending time in a remote village to study local customs and traditions. 3. participant observation research e. Participant observation research involves the researcher becoming actively involved in the group or setting they are studying, while also observing the group's behavior and interactions. f. Application: A researcher working as a waiter in a restaurant while observing staff behavior and customer interactions. 4. field notes g. Field notes are detailed, descriptive records made by the researcher during or after their fieldwork, capturing observations, thoughts, and reflections. h. Application: In ethnographic research, a researcher might take field notes on daily interactions, rituals, and informal conversations observed within a community. Questions: - Compare and contrast: Active Participation and Complete Participation. - Active Participation: Researcher actively engages in group activities but reveals their role as a researcher. Example: A teacher studying student-teacher dynamics while teaching. - Complete Participation: Researcher fully immerses in the group without disclosing their role. Example: A researcher joining a drug-using group without revealing their study. - What are the strengths and weaknesses of participant observation research? - Strengths: Rich, in-depth data from firsthand experience. Flexibility to adapt methods during the study. - Weaknesses: Potential bias and altered group behavior. Time-consuming and limited generalizability. - What are some of the ethical considerations tied to participant observation research? - Informed Consent: Obtaining consent is crucial, especially in active participation. - Deception: In complete participation, not revealing the researcher's role can raise ethical issues. - Privacy and Confidentiality: Protecting participant information is vital. - Impact on Group: Researcher involvement may affect group dynamics and behavior. **[Block 8 ]** Be able to define and apply the following concepts: 1. Respondent  a. A respondent is an individual who provides data or answers to questions in a survey, interview, or questionnaire. b. Application: In a study on college student mental health, the respondents would be the students answering the survey questions. 2. double-barreled questions c. Double-barreled questions are questions that ask about two or more issues at once but only allow for one answer. This can confuse respondents and make the results unreliable. Example: \"How satisfied are you with your job and work-life balance?\" 3. contingency questions d. Contingency questions are follow-up questions that are asked only if the respondent answers a previous question in a certain way. e. Example: \"Have you ever used public transportation?\" If yes, \"How often do you use it?\" 4. response rate f. Response rate is the percentage of respondents who complete and return a survey or questionnaire compared to the total number of people invited to participate. g. Application: A high response rate increases the validity of the study by reducing potential bias from non-respondents. 5. secondary analysis h. Secondary analysis involves using pre-existing data or research for new analysis, instead of collecting new data. i. Application: Analyzing census data to study changes in housing patterns over time. Questions: - Compare and contrast: open-ended to closed-ended questions - Open-ended questions provide richer data but are harder to analyze, while closed-ended questions are easy to analyze but limit responses. - Compare and contrast interview surveys to self-administered surveys - Interview surveys offer in-depth insights but are time-intensive, while self-administered surveys are cost-effective but may lack completeness. - What are the strengths and weaknesses of doing secondary analyses of survey data? - Secondary analysis saves resources but may not fully align with the research objectives. - What are the strengths and weaknesses of survey research compared to other research methods? - Survey research is efficient for large samples but may have response biases and limited depth. - What are some key characteristics of a well-designed survey?  (think beyond formatting) What are some key characteristics of an interview that was well conducted? - A well-designed survey has clear, unbiased questions and a logical flow, while a well-conducted interview requires rapport, active listening, and flexibility.   **[Block 9]** Be able to define and apply the following concepts: 1. purposive sampling a. Purposive sampling (or judgmental sampling) involves selecting participants based on specific characteristics or qualities that are relevant to the research purpose. 2. snowball sampling b. Snowball sampling is a non-probability sampling technique where existing study participants recruit future participants from among their acquaintances. 3. quota sampling c. Quota sampling is a non-random sampling method where researchers ensure that specific subgroups within the population are represented in the sample according to predetermined quotas (e.g., age, gender, ethnicity). 4. simple random sample d. Simple random sampling is a probability sampling technique where every individual in the population has an equal chance of being selected for the sample. 5. systematic sampling with random start e. Systematic sampling with random start involves selecting every k-th individual from a list, with the starting point randomly chosen. Questions: - How should a researcher decide on the size of a sample? - A sample size depends on factors like confidence level, margin of error, variability, and available resources. - How should a researcher go about picking a sample? - The sampling process involves defining the population, choosing the method, determining sample size, and selecting participants. - Compare and contrast probability sampling and nonprobability sampling. - Probability sampling allows for generalization and is statistically rigorous, while nonprobability sampling is more flexible but less reliable for generalization. - Compare and contrast population and study population. - The population includes all individuals of interest, while the study population is the accessible subset available for study. **[Block 10]** Be able to define and apply the following concepts: 1. unobtrusive research a. Unobtrusive research minimizes researcher impact by studying existing data or behavior. 2. content analysis b. Content analysis systematically examines communication content. 3. coding  c. Coding organizes qualitative data into themes for easier analysis. 4. existing sources d. Existing sources are pre-collected data or materials used in research. 5. comparative and historical research e. Comparative and historical research analyzes social phenomena across time and cultures to identify patterns and insights. Questions: - Compare and contrast: manifest and latent content - Manifest content is directly observable, while latent content requires interpretation of underlying meanings. - Compare and contrast: unit of analysis and unit of observation - Unit of analysis refers to what's being studied, and the unit of observation refers to what data is collected from. - What are the strengths and weaknesses of content analysis? - Content analysis is systematic and objective but can be subjective in interpreting hidden meanings, and may miss context. - How does content analysis compare to other methods in terms of reliability and validity? - In terms of reliability, content analysis can be very dependable, while validity depends on the depth and context of the analysis. **[Block 11]** Be able to define and apply the following concepts: 1. quantitative research  a. Quantitative research collects numerical data to examine relationships or patterns. 2. frequency distribution b. Frequency distribution shows how often different values appear in a dataset. 3. bivariate analysis c. Bivariate analysis examines the relationship between two variables. 4. cross tabulation d. Cross tabulation is a table-based method to analyze the relationship between two categorical variables. Questions: - Compare and contrast: continuous and discrete variables - Continuous variables have infinite values within a range, while discrete variables have distinct, countable values. - Compare and contrast: univariate and multivariate analyses - Univariate analysis looks at one variable, while multivariate analysis examines relationships between multiple variables. - Compare and contrast mean, median and mode - Mean is the average, median is the middle value, and mode is the most frequent value. - What are various ways of representing the dispersion in a sample? - Dispersion can be represented by range, variance, standard deviation, and IQR. - Why is it useful to include both the n and the cell percentages in a table? - Including both n and cell percentages in tables provides both absolute and relative context for understanding the data.