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Social Research Methods Final Exam
Questionnaires - This is a collection of questions in which the whole becomes more than the sum of its parts Self-administered Questionnaires - Questionnaires in which respondents are asked to complete the questionnaires by himself Questionnaire Response Rates - The number of people participating in a survey divided by the number selected in the sample (ideal is higher in 70%) Survey Research Purposes - Exploratory, descriptive, explanatory Survey Units of Analysis - Respondents Social Desirability (Type of Bias) - When people answer survey questions through a filter of what will make them look good Contingency Questions - A survey question intended for only some respondents, determined by their responses to some other question Matrix Questions - Questions such as "strongly agree, agree, neutral, disagree, strongly disagree" Telephone Interviews - Pros: 95.5% of households have phones Cons: Unlisted phone numbers/cell phones Random Digital Dialing - A polling method in which respondents are selected at random from a list of 10- digit phone numbers, with every effort made to avoid bias in the construction of the sample. Computer-Assisted Telephone Interviewing - Integrated telephone and computer system in which the interviewer reads the question from a computer screen and enters respondent's answers directly into the computer program. Strengths/Weaknesses of Surveys - Pros: Describing large populations, flexibility, standardized questions Cons: Round pegs in square holes, seldom deal with context of social life, artificial, weak on validity
Ethics of Survey Research - Surveys often ask private information and this must be kept confidential. Questions may cause psychological discomfort. Experiments - Usually involve researchers selecting groups of subjects, doing something to them, and observing the effect Topics Appropriate to Experiments - Hypothesis testing, exploratory topics (not as much descriptive), quantitative research, small group interaction Independent Variable - The stimulus Dependent Variable - The effect Pretesting - Initial measure of the dependent variable along subjects Post-testing - The measurement of a dependent variable among subjects after they have been exposed to an independent variable. Experimental Group - A group of subjects to whom an experimental stimulus is administered Control Group - A group of subjects to whom no experimental stimulus is administered and who should resemble the experimental group in all other respects Double-Blind Experiment - Neither the subjects nor the experimenters know which is the experimental or control group Probability Sampling - a method used by pollsters to select a representative sample in which every individual in the population has an equal probability of being selected as a respondent Randomization - (Probability Sampling) The selection, assignment, or arrangement of elements by chance. Matching - (Probability Sampling) In connection with experiments, the procedure whereby pairs of subjects are matched on the basis of their similarities on one or more variables and one member of the pair is assigned to the experimental group and the other to the control group.
The problem of social research subjects potentially reacting to being studied, so ultimately change their behavior from what it would have normally been Paradigms of Field Research -
- Naturalism
- Ethnography
- Ethnomethodology
- Grounded Theory
- Case Studies/Extended Case Method
- Institutional Ethnography Naturalism - Based on the assumption that an objective social reality exists and can be observed/reported accurately Ethnography - A report on social life that is focused on detailed descriptions rather than explanations Ethnomethodolgy - Focuses on the discovery of implicit, usually unspoken assumptions and agreements (for example, breaching experiments); studying technique that deliberately disrupt social norms and observe the individuals attempt to restore normancy Grounded Theory - Social theory that is rooted in observation of specific, concrete details; focused on an inductive approach that attempts to generate a theory from constant comparing of unfolding observations Extended Case Method - A technique in which case study observations are used to discover flaws and to improve existing social theories Institutional Ethnography - A research technique in which the personal experiences of individuals are used to reveal power relationships and other characteristics of the institutions within which they operate Participatory Action Research - An approach to social research in which the people being studied are given control over the purpose and procedures of the research Focus Groups - Directed talks with a representative sample of a community, and do not involve direct conversations with individual community members Qualitative Interview - Contrasted with survey interviewing, the qualitative interview is based on a set of topics to be discussed in depth rather than based on the use of standardized questions
Strengths and Weaknesses of Field Research - Pros: Finds subtle nuances, greater validity than surveys and experiences Cons: No appropriate statistical analyses, potential problems with reliability Content Analysis - Study of recorded human communication (books, websites, paintings, laws, etc.) Strengths and Weaknesses of Content Analysis - Pros: Permits the study of processes over time, research has little effect on subjects, reliability Cons: Limited recorded communication, validity Big Data - A collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications (ex. NSA, Google, Amazon, etc.) Secondary Analysis - A research method in which researchers use existing material and analyze data that were originally collected by others
- Potential cost in validity if this is used Analysis of Existing Statistics - Type of unobtrusive research that relies on data gathered earlier by someone else for some other purpose (different from secondary analysis); uses big data Evaluation Research - Research undertaken for the purpose of determining the impact of some social intervention, such as a program aimed at solving a social problem (ex. consequences of liberalized marijuana laws) Assessment Studies - Studies that aim to determine the existence and extent of problems, typically among a segment of the population Cost-Benefit Studies - Studies that determine whether the cost of a program can be justified by its expense Monitoring Studies - Studies that provide a steady flow of information about something of interest, such as crime rates or outbreak of an epidemic Program Evaluation Studies - The determination of whether a social intervention is producing the intended result (also known as Outcome Assessment Studies) Types of Evaluation Research Designs -
- Experimental: Just like in chapter 8
- Quasi-Experimental: non-rigorous, lack pre/post testing and control groups
- Time Series Design: measurement over time
Latent Content - The underlying meaning of communication Open Coding - The grouping of qualitative data into categories that seem logical Axial Coding - analysis of categories and labels after completion of open coding Selective Coding - in GTM, this builds on the results of open coding and axial coding to identify the central concept that organizes the other concepts that have been identified in a body of textual materials Memoing - Writing memos that become part of the data or analysis in qualitative research. May describe and define concepts, deal with methodology issues, or offer initial theoretical formulations Code Notes - Examples of memoing; identify the code labels and their meanings Theoretical Notes - Examples of memoing; attempt to attach meaning to the observations (ex: why gangs do what they do) Operational Notes - Examples of memoing; focus on data collection circumstances Qualitative Data Analysis Programs - Unlike quantitative analysis, which seeks to empirically describe data and test specific hypothesis, qualitative data analysis is focused on developing meaning from data Codebook - A guide for the qualitative analysis that outlines individual codes with definitions, criteria for inclusion, and examples Central Tendency - Univariate analysis; mean, median, mode Dispersion - The distribution of values around some central value, often the average Standard Deviation - A computed measure of how much scores vary around the mean; 68% within 1, 95% within 2, 99.9% within 3
Continuous Variable - A variable (such as age, test score, or height) that can take on a wide or infinite number of values, but form a steady progression. Discrete Variable - A variable in which the units are in the whole numbers, or "discrete" units (for example, number of children, number of defects). Bivariate Table - Table that illustrates the relationship between two variables by displaying the distribution of one variable across the categories of a second variable. Contingency Table - Displays counts, and, sometimes, percentages of individuals falling into named categories on two or more variables. The table categorizes the individuals on all variables at once, to reveal possible patterns in one variable that may be contingent on the category of the other Elaboration Model - The initially observed relationship between two variables is mediated by a third variable Test (Control) Variable - "Third" Variable; held constant to clarify further the relationship between two variables Partial Relationship - The relationships observed after the control variable has been taken into account Zero-order Relationship - Just the relationship between one IV and one DV Explanation - Elaboration Model: when Control variable reveals a spurious relationship between original two variables Replication - Elaboration Model: when Control variable reveals actual relationship between two variables Interpretation - Elaboration Model: when Control variable is mediating factor between relationship of two variables Specification - Elaboration Model: when Control variable facilitates relationship between one group of zero-order relationships, but not others Suppressor -
Partial Regression Analysis - Effects of one or more variables are held constant, similar to logic of the elaboration model Curvilinear Regression Analysis - Allows relationships among variables to be expressed with curved geometric lines instead of straight ones Regression Line - Y' = a + bx Inferential Statistics - Procedures used to draw conclusions about larger populations from small samples of data Nonsampling Error - All error other than sampling error; also called measurement error Statistical Significance - Scientists have decided that 5% is the cutoff for statistically significant results. This means that in an experiment design, there must be less than a 5% chance that the results occurred by chance. Levels of Significance - In the context of tests of statistical significance, the degree of likelihood that an observed, empirical relationship could be attributed to sampling error Chi Square - Is used with categorical data. Chi square is the squared difference between the observed frequency and the expected frequency, divided by the expected frequency. Based on the null hypothesis t-Test - Measure for judging statistical significance of group means
- Value of t will increase with the size of differences between means
- Value of t will be larger when the size of the sample increases
- Value of t will be larger when variations of values within each group are smaller Type One Error - Where the researcher rejects the null hypothesis when you should have accepted it Type Two Error - Failing to reject the null hypothesis when in fact it is false Path Analysis - Path analysis is a straightforward extension of multiple regression. Its aim is to provide estimates of the magnitude and significance of hypothesised causal connections between sets of variables. This is best explained by considering a path diagram.
Factor Analysis - Statistical procedure designed to discover the independent elements (factors) in any set of data Analysis of Variance - Analysis of variance (ANOVA) is a collection of statistical models used to analyze the differences among group means and their associated procedures (such as "variation" among and between groups) Discriminant Analysis - Discriminant function analysis is used to determine which variables discriminate between two or more naturally occurring groups. For example, an educational researcher may want to investigate which variables discriminate between high school graduates who decide (1) to go to college, (2) to attend a trade or professional school, or (3) to seek no further training or education. For that purpose the researcher could collect data on numerous variables prior to students' graduation. After graduation, most students will naturally fall into one of the three categories. Discriminant Analysis could then be used to determine which variable(s) are the best predictors of students' subsequent educational choice. One-Way Analysis of Variance - A bivariate analysis that seeks to determine which groups on the independent variable differ from each other in terms of some dependent variable Two-Way Analysis of Variance - A multivariate technique which permits the simultaneous examination of more than two variables Log-Linear Models - Data analysis technique based upon specifying models that describe the interrelationships among variables and then comparing expected and observed table-cell frequency Odds-Ratio Analysis - A statistical technique for expressing the relationship between variables by comparing the odds of different occurrences Geographic Information Systems - Analytic technique in which researchers map quantitative data that describe geographic units for a graphic display Time-Series Analysis - Analysis of a change in a variable over time
