A
Ahistorical generalization - a generalization that is not time-concrete. One which applied to all historical period beyond.
Analytic frames - are systematic, detailed sketches of ideas (or social theories) that a researcher develops in order to aid the examination of a specific phenomenon. In effect, an analytic frame articulates an idea in a way that makes it useful in research. The process of analytical framing is primarily but not entirely deductive (Ragin, 1994, 183).
Analytical induction - Originally, the term had a very strict meaning and was identified with the search for "universals" in social life. Universals are properties that are invariant. Today, however, analytic induction is often used to refer to any systematic examination of similarities that seeks to develop concepts or ideas. Rather than seeing analytic induction as a search for universals, a search that is likely to fail, it is better to see it as a research strategy that directs investigators to pay close attention to evidence that challenges of disconfirms whatever images they are developing. As researchers accumulate evidence, they compare incidents or cases that appear to be in the same general category with each other. These comparisons establish similarities and differences among incidents or cases that appear to be in the same general category with each other. These comparisons establish similarities and differences among incidents and thus help to define categories and concepts. Evidence that challenges or refutes images that the researcher is constructing from evidence provides important clues for how to alter concepts or shift categories (Ragin, 1994, 93).
Approach - a theoretically sustained vantage point for analyzing a subject matter. An approach is more encompassing (but generally less precise) than a conceptual framework: it determines the sets of concepts, questions and perspectives of an inquiry. An approach may also be seen as a quasi-theory or as a pretheory, a path to theory. (Sartori, 1984, 73)
B
Bias - in social research is used primarily to describe aspects of a specific research design that may skew findings in some way. Biased measures don’t do a good job of measuring the things they are purported to measure and therefore lack validity; biased samples are not representative of the relevant population or set of cases; and so on (Ragin, 1994, 183).
binary comparisons - Focused comparisons which include only two cases.
Bivariate analysis - The analysis of two variables simultaneously, for the purpose of determining the empirical relationships between them. The construction of a simple percentage table or the computation of a simple correlation coefficient would be examples of bivariate analyses (Babbie, 1998, G1).
C
Category - a concept unifying a number of observations have some characteristics in common (Dey, 1993, 275).
Classification - a process of organizing data into categories or classes and identifying formal connections between them (Dey, 1993, 275). Sartori adds: A classification requires a single criterion which serves as the basis of division. When multiple criteria or dimensions are involved, we have a typology and/or taxonomy. (Sartori, 1984, 73).
Comparative Method - The family of techniques employed in comparative political research" (Hague et al., 1998, 12).
Concept - a general idea which stands for a class of concepts (Dey, 1993, 275).
Conceptual traveling and stretching - The terms reflect the concern in the problem of applying categories across diverse contexts. Conceptual travelling means the application of concepts to new cases. Conceptual stretching reflects the distortion that occurs when a concept does not fit the new cases. Sartori 1970 encourages the scholar to be attentive to context, but without abandoning broad comparison. See also Sartori's guidelines
Control Group - In experimentation, a group of subjects to whom no experimental stimulus is administrate and who should resemble the experimental group in all other respects. The comparison of the control group and the experimental group at the end of the experiment points to the effect of the experimental stimulus (Babbie, 1998, G2).
Control Variable - A variable that is held constant in an attempt to clarify further the relationship between two other variables. Having discovered a relationship between education and prejudice, for example, we might hold gender constant by examining the relationship between education and prejudice among men only and then among women only. In this example, gender would be the control variable (Babbie, 1998, G2).
Counterfactuals -
Correlation - A statistical measure of the closeness of the variations in the value of one variable t the variations in the value of another. The correlation coefficient (r) can take any value between +1 and -1, at which extremes there is perfect correspondence between the variations of the variables. At the value zero, there is no correspondence
Covariation - refers to a pattern of correspondence between two variables. If two variables covary, then particular values on one variable tend to be associated in a systematic way with particular values on another variable (Ragin, 1994).
Critical case - The idea here is that if a proposition can be shown to work when conditions are least favorable for its validity, it is likely to be valid in all other circumstances as well. If democracies are now consolidating in countries which have no previous experience of that form of rule we can be sure that the modern move toward democracy is significant. Alternatively, a proposition which fails to work even in the most favorable conditions can quickly be dismissed. If post-material values are nowhere to be found among graduates in the wealthiest countries, then the theory of post-materialism is no good. Depending on expectations, we can set out either to support a theory by showing its value in unfavorable conditions (a "least favorable" design) or to disprove a theory be showing it fails even in favorable circumstances ( a most favorable design). (Hague et al., 1999).
D
Data -
Primary Data -
Secondary Data -
Deduction - the process of driving more specific ideas or propositions from general ideas, knowledge, or theories and working out their implications for a specific set of evidence or specific kinds of evidence (Ragin, 1994, 186).
Dependent variable - the aspect or attribute of cases or observations that the investigators hopes to explain or in some way account for (Ragin, 1994, 186).
Descriptive statistics - Statistical computations describing either the characteristics of a sample or the relationship among variables in a sample. It merely summarize a set of sample observations, whereas inferential statistics move beyond the description of a specific observations to make inferences about the larger population from which the sample observations were drawn (Babbie, 1998, G2).
Deviation scores - show whether a case is above or below the average value on a variable, and by how much. The average or mean value is first computed over all relevant cases. The deviation score is computed by subtracting the average value from the value for a particular case. (Ragin, 1994, 186).
Dichotomous variable - A variable having only two categories. Also called binomial and/or binary variable (Babbie, 1998, G2).
Dispersion - The distribution of values around some central value, such as an average. The range is a simple example of a measure of dispersion. Thus we may report that the mean age of a group is 37.9, and the range is from 12 to 89 (Babbie, 1998, G2).
Dummy variable - A variable in regression analysis that takes a value of one or zero depending on whether some particular characteristics applies to the observation. For example, in a regression that measures the relationship between weight and height, there might be a sex dummy which takes a value of one for men, and zero for women. This would take account of the possible fact that on average a man of the same height as woman may weigh more.
E
Ecological fallacy - Erroneously drawing conclusions about individuals based solely on the observation of groups (Babbie, 1998, G2).
empiricism
epstimology
Exogenous variable - A variable whose value is not determined with the set of equations, or models, established to make predictions or test a hypothesis.
Explanations -
Extrapolation -
External invalidity - Refers to the possibility that conclusions drawn from experimental results may not be generalizable to the 'real' world (Babbie, 1998, G3). See also Validity.
External validation - The process of testing the validity of a measure, such as an index or scale, by examining its relationship to other, presumed indicators of the same variable. If the index really measures prejudice, for example, it should correlate with other indicators of prejudice. (Babbie, 1998, G3).
F
Face Validity - That quality of an indicator that makes it seem a reasonable measure of some variable. That the frequency of church attendance is some indication of a person's religiosity seems to make sense without a lot of explanation. It has has face validity (Babbie, 1998, G3).
Factor analysis - A complex algebraic method for determining the general dimensions of factors that exist within a set of concrete observations (Babbie, 1998, G3).
Focused comparisons - are comparisons that concentrate on intensive study of an aspects of the cases in a small number of cases (two-to-four cases)
Frequency distribution - (1) A tabulation showing a statistical population allocated numerically into sub-categories of a specified classification. (2) A description of the number of times the various attributes of a variable are observed in a sample. The report that 53% of a sample were men and 47% were women would be a simple example of a frequency distribution. Another example would be the report that 15 of the cities studied had populations under 10,000, 23 had populations between 10,000 and 25,000, and so forth. (Babbie, 1998, G3).
Functionalism - A paradigm that focuses on the functions served by the elements making up a whole system or organism. Thus, one of the functions of higher education is to keep young people out of the job market (Babbie, 1998, G3).
Functional equivalence - The notion of functional equivalence descends from the idea that every political system necessarily fulfills certain fundamental tasks. The same tasks may be performed however by different structures while the same structures may fulfill, in different countries, different tasks.
Two institutions or processes are functionally equivalent when they fulfill the same role within the political system. Institutions with the same function not necessarily perform exactly the same functions; monarchs my rule with a rod of iron or just dispense medals to worthy citizens. Also, the same function can be performed by difference processes; For example, elections and revolutions a devices for repealing the governing elite" (Hague et al., 1998, 274).
Read more: Dogan Matttei and Pelassy Dominique, How to Compare nations: Strategies in Comparative Politics, Chatham House Publishers, New Jersey, 1984, pp. 31-37.
G
Generalizability - That quality of a research finding that justifies the inference that it represents something more than the specific observations on which it was based. If you discover why people commit burglaries, can you generalize that discovery to other crimes as well? (Babbie, 1998, G3).
Gini coefficient - a coefficient based on the Lorenz curve showing the degree of inequality in a frequency distribution such as personal income. It measured as the area between Lorenz curve and 45 degrees Divided in the area above the 45 degrees line.
If the frequency distribution is equal, the Lorenz curve coincides with the 45 degrees line, and G=0
H
Heuristic case studies -
Hypothesis - (1) a specific proposition or "educated guesses" regarding what researchers expect to find in a body of evidence, based on their substantive and theoretical knowledge. In standard applications of the scientific method, hypotheses are tested with data specifically collected for the hypotheses (Ragin, 1994, 187).
(2) a theoretical explanation of the behavior of phenomena which can be tested against the facts.A hypothesis can be refuted, unlike a tautology, which is true by definition, but it may not be possible to prove that it is correct.
Null hypothesis -
I
Ideal Types - 1. An ideal type is an analytical construct that serves as a measuring rod for social observers to determine the extent to which
concrete social institutions are similar and how they differ from some defined measure. The ideal type involves determining
the "logically consistent" features of a social institution. The ideal type never corresponds to concrete reality but is a description
to which we can compare reality. "Ideal Capitalism," for example, is used extensively in social science literature.
According to the ideal type, capitalism consists of four basic features: Private Ownership; Pursuit of Profit; Competition;
Laissez Faire. In reality, all capitalist systems deviate from the theoretical construct we call "ideal capitalism."
But the construct allows us to compare and contrast economic systems of various societies to this definition. Source: Max Weber Home-Page
2. In order to conceptualized and generalized historical events and processes despite their uniqueness, Max Weber, suggested the construction of "ideal type": concepts that are constructed by the researchers (and thus are not "real") and capture the basic characteristics of a series of cases. This abstract construct is called "ideal type". And Sartori adds: ideal types are heuristic construct that does not reflect frequency or probability of empirical occurrence. When construed as a polar end of a continuum or of a serial order, it coincides with a polar concept. When construed as a parameter or model (archetype) an ideal type is also called "pure type". (Sartori, 1984, 78)
Independent variable - 1. are also known as causal variables. When one variable is used to explain or account for the variation in another variable, it is called causal or independent. Variation in levels of nutrition, for example, may be used as an independent variable to account for variation in average life expectancy across countries (Ragin, 1994, 188).
2. A variable from which the values of other variables are derived.
Indicator - An observation that we choose to consider as a reflection of a variable we wish to study. Thus for example, attending church might be considered an indicator of religiosity. (Babbie, 1998, G3).
Indirect experiment - Because experiments are powerful tools for scientists and because in most social domains experimentation cannot be applied we have to look for substitutes. In an indirect experiment, we try to identify situations and events which will help us to exhaust the logically possible combinations of variation which we usually use in controlled experimentation.
Induction - the process of using evidence to formulate or reformulate a general idea. Generally, whenever evidence is used as a basis for generating concepts , as in qualitative research, or empirical generalizations, as in quantitative research, induction has played a part. (Ragin, 1994, 188).
inference - "is the process of using the facts we know to learn about facts we do not know. The facts we do not know are the subjects of our research questions, theories, and hypotheses. The facts we do know form our (quantitative or qualitative) data or observations" (King et al., 1994, 46).
Inferential statistics - The body of statistical computations relevant to making inferences from findings based on sample observations to some larger population. See also Informant - Someone well versed in the social phenomenon that you wish to study and who is willing to tell you what he or she knows. If you were planning participant observation among the members of a religious sect, you would do well to make friends with someone who already knows about them - possibly a member of the sect - who could give you some background information about them. Not to be confused with a respondent(Babbie, 1998, G4).
Internal invalidity - Refers to the possibility that the conclusions drawn from experimental results may not accurately reflect what went on in the experiment itself. See also external validity and validity (Babbie, 1998, G4).
Internal validation - The process whereby the individual items composing a composite measure are coreleated with the measure itself. This provides one test of the wisdom of including all the items in the composite measure (Babbie, 1998, G4).
Inverse relationship -
Interpolation -
Interpretation - A technical term used in connection with the elaboration model. It represents the research outcome in which a control variable is discovered to be the mediating factor through which an independent variable has its effect on a dependent variable (Babbie, 1998, G4).
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, since the distance between 17 and 18 is the same as that between 89 and 90. See also nominal measure, ordinal measure, and ratio measure (Babbie, 1998, G4).
Invariance - the quality of being constant, unchanging.
Interview - A data-collection encounter in which one person asks questions of another. Interviews may be conducted fact-to-face or by telephone. (Babbie, 1998, G4).
Judgment al sample - A type of nonprobability sample in which you select the units to be observed on the basis of your own judgment about which ones will be the most useful or representative. Another name for this is purposive sample (Babbie, 1998, G4).
Least favorable research design - seeks to test a theory in the crucial circumstances where it is least likely to hold up. See also the most favorable design.
Level of significance - In the context of tests of statistical significance, the degree of likelihood that an observed, empirical relationship could be attributable to sampling error. A relationship is significant at the 0.05 level if the likelihood of its being only a function of sampling error is no greater than 5 out of 100.(Babbie, 1998, G4).
Longitudinal Study - A study design involving the collection of data at different points in time (Babbie, 1998, G4).
Macro-theory - 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 macro-theory (Babbie, 1998, G4).
Mean - An average, computed by summing the values of several observations and dividing by the number of observations (Babbie, 1998, G4).
Measures - are implementations of variables in a particular set of data. Generally every variable may be measured in a variety of ways, and researchers must justify the specific measures they use for each variable (Ragin, 1994, 189).
Median - Another average, representing the value of the "middle" case in a rank ordered set o observations. If the ages of five men are 16, 17, 20, 54, and 88, the median would be 20 (The mean would be 39) (Babbie, 1998, G4).
Meso-theory - A theory aimed at understanding social and political life at the intermediate level of political institutions and in regards to specific aspects of the macro
Methodological Individualism - A methodological approach that holds that all description and explanation of social phenomena should ultimately be in terms of individuals, their properties and their interrelations in terms of their properties (source: Franssen, 1997, 10). And in a similar formulation: The elementary unit of social life is the individual human action. To explain social institutions and social change is to show how they arise as the result of the action and interaction of individuals (Elster, 1989, 13).
Micro-theory - A theory aimed at understanding social and political life at the intimate level of individuals and their interactions. Examining how the play behavior of girds differs from that of boys would be an example of micro-theory (Babbie, 1998, G5).
Minimal definition - a definition that includes the defining properties (or characteristics) and excludes the accompanying properties. See also Parsimony. (Sartori, 1984, 79)
Mode - Still another average, representing the most frequently observed value or attribute. If a sample contains 1,000 Protestants, 275 Catholics, and 33 Jews, Protestant is the modal category. (Babbie, 1998, G5).
Model - (1) a drastically simplified representation of the real world endowed with strong explanatory power; or (2) an exemplary, paradigmatic, idealized case. (Sartori, 1984, 79)
The most favorable research design - seeks initial support for a theory by testing it in favorable conditions.
A Most Different System Design - compares as contrasting cases as possible in order to show the robustness of a relationship between dependent and independent variables. Such a design assumes that by demonstrating that the observed relationships hold in a range of contrasting settings the argument of the research is better supported
A Most Similar System Design - compares similar cases as possible on the assumption that the more similar the cases being compared, the more possible it should be to isolate the factors responsible for differences between them.
Multiple causation -
Multiple correlation coefficient - A statistical measure of the accuracy by which a known variable is estimated by an equation, or model, containing two or more independent variables. It can take values between zero and one. At zero, there is no correspondence at all between the predicated and actual variable, and at unity the coefficient indicates a perfect correspondence. Also called the Coefficient of determination and R-squared (Bannock et al., 1992, 297).
Multivariate analysis - The analysis of the simultanoeus relationships among several variables Examining simultaneously the effects of age, gender, and social class on religiosity would be an example of multivariate analysis (Babbie, 1998, G5).
Necessary condition - in causal explanation a condition in the absence of which an event (effect) cannot occur. A necessary condition is not sufficient for an event to occur or for a thing to exist. See also, Sufficient condition. (Sartori, 1984, 79)
Negative Correlations - exists when high values on one variable tend to be paired with low values on another variable and vice versa. For example, rates of literacy and infant mortality are two variables that are negatively correlated across countries (Ragin, 1994, 189).
Nominal measure - A level of measurement describing a variable the different attributes of which are only different, as distinguished from ordinal, interval, or ratio measures. Gender would be an example of nominal measure (Babbie, 1998, G5).
Nomothetic - An approach to explanation in which we seek to identify a few causal factors that generally impact class of conditions or events. Imagine the two or three key factors that determine which colleges students choose, such as proximity , reputation, and so forth (Babbie, 1998, G5).
Normative statements - statements that are neither factual nor hypothetical (Sartori, 1984, 79)
Null hypothesis - Hypothesis that suggests there is no relationship among the variables under study. You may conclude that the variables are related after having statistically rejected the null hypothesis (Babbie, 1998, G5).
Operational definition - (1) The concrete and specific definition of something in terms of the operations by which observations are to be categorized (Babbie, 1998, G5). (2) an extensional definition hinged on measurable properties and leading to measurement operations. More broadly, a definition that establishes the meaning of the variable in terms of observable-measurable indicators. (Sartori, 1984, 80).
Operationalization - One step beyond conceptualization. It is the process of developing operational definitions (Babbie, 1998, G5).
Ordinal measure - A level of measurement describing a variable with attributes you can rank-order along some dimension. An example would be socio-economic status as composed of the attributes of high, medium, low. See also, nominal, interval, or ratio measures. Gender would be an example of nominal measure (Babbie, 1998, G5).
Paradigm - In Thomas Kuhn’s sense, the scientific community consensus on what constitutes the scientific procedure, and the basic axioms or findings thus resulting. More loosely, a framework that gives organization and direction to scientific investigation (Sartori, 1984, 80).
Parsimony - in quantitative social research refers to the use of as few independent variables as possible to explain as much of the variation in a dependent variable as possible (Ragin, 1994, 189).
Parsimony (in definitions) - a definition that includes only the necessary properties of a concept (Sartori, 1984, 81)
Path analysis - A form multivariate analysis in which the causal relationships among variables are presented in graphic format (Babbie, 1998, G5).
Path dependence - describes a process which can lead to several stable outcomes, depending on options selected early in the process. For example, the success of democratization may depend critically on the details of the constitution established during the transition from the old regime. However, if underlying factors (for example, strong elite support for democracy) mean that the new democracy will consolidate come what may, the process is path-independent. Case study analysis often exaggerate path-dependence but statistical studies generally ignore it altogether (Bresslin et al., 1999, 276).
Positive correlations - exist when high values on one variable tend to be paired with high values on another and low values tend to be paired with low values. For example, nutrition levels and average life expectancy are two variables that are positively correlated across countries. (Ragin, 1994, 189).
Prediction - is the use of accumulated social scientific knowledge about general patterns and past events to make projections or extrapolation about the future and other novel institutions. Generally, social researchers can make projections about rates and probabilities, but not about specific events, like the timing of a major political change (Ragin, 1994, 189-90).
Present-absence dichotomise - are variables that have two values, one indicating that a condition or feature is present, the other indicating that it is absent. The comparative analysis of configurations focuses on combinations of presence-absence dichotomise (Ragin, 1994, 190).
Probability sample - The general term for a sample selected in accord with probability theory, typically involving some random-selection mechanism (Babbie, 1998, G5).
Qualitative data - data which deals with numbers rather than meanings (Dey, 1993, 276).
Qualitative research - is a basic strategy of social research that usually involves in-depth examination of a relatively small number of cases. Cases are examined intensively with techniques designed to facilitate the clarification of theoretical concepts and empirical categories (Ragin, 1994, 190).
Quasi-experiment - In an experiment, subjects are pre-tested and then randomly assigned to a treatment group or a control group. In a post-test, the two groups are compared to ascertain the impact of the treatment. True experiments must be constructed but comparative politics can occasionally take advantage of naturally-occurring quasi-experiments to draw inferences about the impact of a particular variable (for example, electoral reform) (Hague et al., 1999, 279).
Quantitative data - data which deals with numbers rather than meanings (Dey, 1993, 276).
Quantitative research - is a basic strategy of social research that usually involves analysis of patterns of covariation across a large number of cases. This approach focuses on variables and relationships among variables in an effort to identify general patterns of covariation (Ragin, 1994, 190).
Questionnaire - A document containing questions and other types of items designed to solicit information appropriate to analysis. Questionnaires are used primarily in survey research and also in experiments, field research, and other modes of observation.
Random sample - a sample in which every member of the population (simple random sample_ or some subset of the population (stratified sample) being tested has an equal chance of being included in the sample. The purpose of sampling is to be able to infer, from the sample taken, the attributes of the population as a whole. Only if the sample is random can the probability be calculated that a sampled attribute applies to the population as a whole.
Ratio Measure - A level of measurement describing a variable the attributes of which have all the qualities of
ordinal, interval, or nominal measures and in addition are based on a "true zero" point. Age would be an example of a ratio measure (Babbie, 1998, G6).
Reductionism - strict limitation (reduction) of the kinds of concepts to be considered relevant to the phenomenon under study (Babbie, 1998, G6).
Regression analysis - A mathematic technique for estimating the parameters of an equation from sets of data of the independent and dependent variables. For instance, in the equation q = aY+bP+ c, the parameters a, b, c can be estimated, provided there is sufficient number of actual observations of the variables, q, Y and P.
Reification - The process of regarding things that are not real as real (Babbie, 1998, G6).
Reliability - (1) That quality of measurement method that suggests that the same data would have been collected each time in repeated observations of the same phenomenon (Babbie, 1998, G6); (2) the extent to which measurements yield, when repeated, similar or confirming results (Sartori, 1984, 82).
Replication - Generally, the duplication of an experiment to expose or reduce error. It is also a technical term used in connection with the elaboration model, referring to the elaboration outcome in which the initially observed relationship between two variables persists when a control variable is held constant (Babbie, 1998, G6).
Research design - is a plan for collecting and analyzing evidence that will make it possible for the investigator to answer whatever questions he or she has posed. The design of an investigation touches almost all aspects of the research, form the minute details of data collection to the selection of the techniques of data analysis (Ragin, 1994, 191).
Research strategies - combine a primary research objective and a specific research method, for example, the sue of comparative methods to study diversity. Each strategy constitutes a specific way of linking ideas and evidence to produce a representation of some aspect of social life (Ragin, 1994, 191).
Retroduction - is the interplay of induction and deduction, and is central to the process of scientific discovery. The process of constructing representations form the interaction between analytic frames and images involves retroduction (Ragin, 1994, 191).
Standard deviation - (1) A measure of the spread of a series of values of a variable around its mean. It is defined as the square root of the variance. Stratified sample - A method of sampling which is used when the population to be sampled is not homegenous and the nature of the population's heterogeneity is pertinent to the characteristic of the population about which information is sought. Suppose we wish to find out the percentage of households (the population) which owns dish-washers. Households are not homogeneous; they may be classified into subgroups or strata by, for instance, social group, or income level and, moreover, these subgroups are likely to differ in their ownership of consumer durables, such as dish-washers. Rather than take a random sample of the whole population of households, the latter is first subdivided into the appropriate categories or strata and random samples taken from each. If the population is heterogeneous a stratified sample will give more accurate results than a simple random sample of the same size.
Statistical Significance - the unlikeliness that relationships observed in a sample could be attributed to sampling error alone (Babbie, 1998, G7).
Sufficient condition - in causal explanation, that condition which suffices to bring a thing into existence or to generate an event (effect). Note that the event can occur on account of many, different sufficient conditions (i.e., a given sufficient condition is neither exclusive or exhaustive). (E.g., lack of oxygen is a sufficient condition of death; but death can occur on account of many other conditions" (Sartori, 1984, 84)
Tautology - literally, saying the same thing (Sartori, 1984, 84).
Theoretical sampling - A deliberate selection of cases. Theoretical sampling describes the process of choosing new research sites of cases to compare with one that has already been studied. For example, a researcher interested in how environmental activists in the United States maintain their political commitments might extend the study to (1) environmental activists in another part of the world or perhaps to (2) another type of activist. The goal of theoretical sampling is not to sample in a way that captures all possible variations, rather in one that aids the development of concepts and deepens the understanding of research subjects (Ragin, 1994, 98).
Theory - a system of ideas which conceptualizes some aspect of experience (Dey, 1993, 276). Compare with Sartori - a body of systematically related generalizations of explanatory value (Sartori, 1984, 84)
Theory - middle range theory Theorizing can be performed at several levels of social inquiry. The midpoint between micro-level and macro-level theories is where middle-range theories are located. Robert Merton suggested that middle-range theories represent the most constructive effort for theorizing. It is in the middle between the minor working hypotheses and the all-inclusive speculations were one can hope to derive a very large number of empirically observed uniformities of social behavior.
Truth tables - are used in the comparative analysis of configurations of similarities and differences to summarize the different patterns that exist in a set of cases. It summarizes a data matrix by sorting cases according to their combinations of values on dichotomous causal variables (Ragin, 1994, 193).
Typology - The classification of observations in terms of their attributes on two or more variables. The classification of newspapers as liberal-urban, liberal-rural, conservative-urban or conservative-rural would be an example (Babbie, 1998, G7).
Units of analysis - The whator whom being studied. In social science research, the most typical units of analysis are individual people (Babbie, 1998, G7).
Univariate analysis - The analysis of a single variable, for purposes of description. Frequency distributions, averages, and measures of dispersion would be examples of univariate analysis, as distinguished from bivariate and multivariate analysis (Babbie, 1998, G7).
Validity - refers to the appropriateness of a measure - does it measure what it is supposed to measure?. To assess validity researchers must assess whether their data collection and measurement procedures work the way they claim (Ragin, 1994, 193).
Validation - the process by which scientific theories become accepted.
Variable - a concept which varies by kind or amount (Dey, 1993, 276).
Variance - A measure of the degree of dispersion of a series of numbers around their mean. The larger the variance the greater the spread of the series around its means.
Verification - testing the empirical validity of assertions, generalizations, laws and theories. Since the number of supporting instances is indefinite, a process of verification is never final(Sartori, 1984, 85)
Weighting - A procedure employed n connection with sampling whereby units selected with unequal probabilities are assigned weights in such a manner as to make the sample representative of the population from which it was selected (Babbie, 1998, G7).
Do you have difficulties with some words? Use Sources:
Babbie Earl, The Practice of Social Research, 8th edition, Wasdworth Publishing Company, 1998.
Dey, Ian Qualitative Data Analysis, Rutledge, 1993.
Dogan Matttei and Pelassy Dominique, How to Compare nations: Strategies in Comparative Politics, Chatham House Publishers, New Jersey, 1984, pp. 5-6.
Elster, Jon Nuts and Bolts for the Social Sciences, Cambridge University Press, 1989.
Franssen, Maarten, Some Contributions to Methodological Individualism in the Social Sciences, Phd Dissertation, University of Amsterdam, 1997.
Hague, Rod, Harrop Martin and Breslin Shaun, Comparative Government and Politics: An Introduction, fourth edition, macmillan, 1998.
Ragin Charles, Constructing Social Research, Pine Forge Press, Sage, Thousand Oaks, CA, 1994.
Sartori, Giovanni (ed.), Social Science concpets, Sage Publications, 1984.
J
L
M
N
O
P
Q
Open-ended questions -
Closed-ended questions -
R
S
(2) is a statistic concept that is used to describe how much the typical case departs or differs from the mean or average value of a particular variable, computed across all cases. (Ragin, 1994, 193).
T
U
V
See also intervening, dependent and independent variables
W
Webster Dictionary on-line Or use / download the Babylon Translation Software
