T his paper aims to clarify the meaning, and explain the utility, of the case study method, a method often practiced but little understood. A “case study,” I argue, is best de? ned as an intensive study of a single unit with an aim to generalize across a larger set of units. Case studies rely on the same sort of covariational evidence utilized in non-case study research. Thus, the case study method is correctly understood as a particular way of de? ning cases, not a way of analyzing cases or a way of modeling causal relations.
I show that this understanding of the subject illuminates some of the persistent ambiguities of case study work, ambiguities that are, to some extent, intrinsic to the enterprise. The travails of the case study within the discipline of political science are also rooted in an insuf? cient appreciation of the methodological tradeoffs that this method calls forth. This paper presents the familiar contrast between case study and non-case study work as a series of characteristic strengths and weaknesses—af? nities— rather than as antagonistic approaches to the empirical world.
In the end, the perceived hostility between case study and non-case study research is largely unjusti? ed and, perhaps, deserves to be regarded as a misconception. Indeed, the strongest conclusion to arise from this methodological examination concerns the complementarity of single-unit and cross-unit research designs. tion of work generated by the discipline, the case study method is held in low regard or is simply ignored. Even among its defenders there is confusion over the virtues and vices of this ambiguous research design.
Practitioners continue to ply their trade but have dif?culty articulating what it is that they are doing, methodologically speaking. The case study survives in a curious methodological limbo. How can we understand the profound disjuncture that exists between the case study’s acknowledged contributions to political science and its maligned status within the discipline? If case studies are methodologically ? awed, why do they persist?
The paper is divided into two parts. The ? rst part focuses on matters of de? nition. I argue that for methodological purposes a case study is best de?ned as an in-depth study of a single unit (a relatively bounded phenomenon) where the scholar’s aim is to elucidate features of a larger class of similar phenomena. It is demonstrated that case studies rely on the same sort of covariational evidence utilized in non-case study research.
Thus, the case study method is correctly understood as a particular way of de? ning cases, not a way of analyzing cases or a way of modeling causal relations. I show, ? nally, that this understanding of the subject illuminates some of the persistent ambiguities of case study work, ambiguities that are, to some extent, intrinsic to the enterprise.
In the second part of the paper I proceed to examine the contrast between case study and non-case study work. The central argument here is that the differences between these two genres are best understood as characteristic strengths and weaknesses—af? nities—rather than antagonistic approaches to the empirical world. Tradeoffs, rather than dichotomies, characterize the ongoing case study/non-case study debate. T he case study occupies a vexed position in the discipline of political science.
On the one hand, methodologists generally view the case study method with extreme circumspection (Achen and Snidal 1989; King, Keohane, and Verba 1994; Lieberson  1992, 1994; Njolstad 1990). A work that focuses its attention on a single example of a broader phenomenon is apt to be described as a “mere” case study. At the same time, the discipline continues to produce a vast number of case studies, many of which have entered the pantheon of classic works (Allen 1965; Allison 1971; Dahl 1960; Johnson 1983; Kaufman 1960; Lazarsfeld, Berelson, and Gaudet 1948; Lijphart 1968; Pressman and Wildavsky 1973).
Judging by recent scholarly output, the case study method retains considerable appeal, even among scholars in research communities not traditionally associated with this style of research—e. g. , among political economists and quantitatively inclined political scientists (Acemoglu, Johnson, and Robinson 2003; Bates et al. 1998; Rodrik 2003). By the standard of praxis, therefore, it would appear that the method of the case study is solidly ensconced and, perhaps, even thriving.
Thus, a paradox: Although much of what we know about the empirical world is drawn from case studies and case studies continue to constitute a large propor-John Gerring is Associate Professor, Department of Political Science, Boston University, 232 Bay State Road, Boston, MA 02215 (jgerring@bu. edu).
Helpful comments were received from Robert Adcock, Andrew Bennett, Henry Brady, Bear Braumoeller, David Collier, Michael Coppedge, Colin Elman, Peter Hall, Alan Jacobs, Evan Lieberman, Jim Mahoney, Jason Seawright, David Waldner, and three anonymous reviewers for the journal. William Barndt and Joshua Yesnowitz provided crucial assistance at the ? nal stages of manuscript preparation.
George and Bennett 2004 reached me in manuscript form as I was developing the ideas for this paper and had a substantial impact on my own understanding of the case study—although some differences of opinion remain. Funding for this research was generously provided by the Frederick S. Pardee Center for the Study of the Longer-Range Future. Work was completed while the author was in residence at the School of Social Science, Institute for Advanced Study. WHAT IS A CASE STUDY? What is a case study, and how is it differentiated from other styles of research? Regretfully, the term “case 341.
What Is a Case Study? May 2004 study” is a de? nitional morass. To refer to a work as a case study might mean (a) that its method is qualitative, small-N (Yin 1994); (b) that the research is ethnographic, clinical, participant-observation, or otherwise “in the ? eld” (Yin 1994); (c) that the research is characterized by process-tracing (George and Bennett 2004); (d) that the research investigates the properties of a single case (Campbell and Stanley 1963, 7; Eckstein  1992); or (e) that the research investigates a single phenomenon, instance, or example (the most common usage).
Evidently, researchers have many things in mind when they talk about case study research. 1 As a result of this profusion of meanings, proponents and opponents of the case study marshal a wide range of arguments but do not seem any closer to agreement than when this debate was ? rst broached several decades ago. How, then, should the case study be understood? The ? rst three options enumerated above (a–c) seem inappropriate as general de? nitions of the topic since each implies a substantial shift in meaning relative to established usage.
One cannot substitute case study for qualitative, ethnographic, or process-tracing without feeling that something has been lost in translation. These de? nitions are best understood as describing certain kinds (subtypes) of case studies, rather than the general phenomenon itself. The fourth option (d) equates the case study with the study of a single case, the N = 1 research design. This is simply wrong, as argued at length below; case studies always employ more than one case. The ? fth option (e), centering on phenomenon, instance, or example as the key term, is correct as far as it goes but also ambiguous.
Imagine asking someone, “What is your instance? ” or “What is your phenomenon? ” A case study presupposes a relatively bounded phenomenon, an implication that none of these terms captures. As a substitute for these ? awed de? nitions, I propose to de? ne the case study as an intensive study of a single unit for the purpose of understanding a larger class of (similar) units. A unit connotes a spatially bounded phenomenon—e. g. , a nation-state, revolution, political party, election, or person—observed at a single point in time or over some delimited period of time.
(Although the temporal boundaries of a unit are not always explicit, they are at least implicit. )2 To clarify this de? nition we must establish the relationship of the case study, so de? ned, to other terms in this crowded semantic ? eld. Following is a set of nested de? nitions, which should be read carefully. A “population” is comprised of a “sample” (studied cases), as well as unstudied cases. A sample is comprised of several “units,” and each unit is observed at discrete points in time, comprising “cases. ” A case is comprised of several relevant dimensions (“variables”), each of which is built upon an “observation” or observations.
1 For those familiar with the rectangular form of a dataset it may be helpful to conceptualize observations as cells, variables as columns, cases as rows, and units as either groups of cases or individual cases (depending upon the proposition and the analysis). The most important point is that all these terms are de? nable only by reference to a particular proposition and a corresponding research design.
A country may function as a case, a unit, a population, or a case study. It all depends upon what one is arguing. In a typical cross-country time-series regression analysis (e. g. , Przeworski et al.2000), units are countries, cases are country-years, and observations are collected for each case on a range of variables. However, shifts in the unit of analysis of a proposition change the referential meaning of all terms in the semantic ? eld.
If one moves down one level of analysis the new population lies within the old population, the new sample within the old sample, and so forth, such that an observation in the original proposition now becomes a case. Population, unit, case, and observation are nested within each other. Since most social science research occurs at several levels of analysis these terms are generally in ux. Nonetheless, they have distinct meanings within the context of a single proposition, which de? nes the principal unit of analysis.
I do not issue this somewhat novel de? nition of case study (an intensive study of a single unit for the purpose of understanding a larger class of units) with any hopes of displacing common usage. Indeed, there is no harm in continuing to refer to a case study in the various ways listed above (options a–e). What is important is that we have recourse to a narrower and clearer de? nition when methodological confusions arise so that we have a way to arbitrate such confusions.
The de? nition chosen here is useful in this regard. Moreover, it captures the essential features of other extant de? nitions; it is resonant (Gerring 2001, chap. 3). Finally, as the succeeding portions of this paper show, it clari? es the distinctive features of a broad class of work in the discipline of political science and in neighboring ? elds of the social sciences. It is theoretically useful. The Case Study Method Considered as an Empirical Endeavor The distinctiveness of the case study is most clearly understood when placed within a broader set of methodological options.
To understand what a case study is, one must comprehend what it is not. All empirical evidence of causal relationships is covariational in nature. A purported cause and effect must be found to covary. They must appear and disappear, wax and wane, or perform some other transformation in tandem or at some regular, more or less predictable, intervals. Even where this covariation is imagined, as in a counterfactual thought experiment, the evidence we imagine is of a covariational sort. Conversely, the absence of such covariation is taken as discon? rming evidence.
If the appearance and disappearance (waxing/waning et al. ) of X and Y are not associated In addition to sources cited above, see Brady and Collier 2004, Campbell (1975) 1988, Davidson and Costello 1969, Feagin, Orum, and Sjoberg 1991, George 1979, McKeown 1999, Ragin 1987, 1997, Ragin and Becker 1992, and the symposium, “The Case Study Method in Sociology,” in Current Sociology, Volume 40, Number 1 (Spring 1992). 2 Similar understandings of the term “unit” can be found elsewhere (e. g. , King, Keohane, and Verba 1994, 76–77). 342 American Political Science Review Vol. 98, No. 2.
TABLE 1. Research Designs: A Covariational Typology Temporal Variation None (1 unit) Within-unit Across-unit Across- and within-unit No [Logically impossible] (b) Case study II (d) Cross-sectional (f) Hierarchical Yes (a) Case study I (c) Case study III (e) Time-series cross-sectional (g) Hierarchical time-series; Comparative-historical Spatial Variation in any way that can be rationally explained, and hence predicted (or postdicted), then the empirical evidence suggests that a causal relationship does not exist. 3 This provides a useful way of typologizing various research designs.
Covariation may be observed (a) in a single unit diachronically, (b) within a single unit synchronically, (c) within a single unit diachronically, (d) across units synchronically, (e) across units synchronically and diachronically, (f) across and within units synchronically, or (g) across and within units synchronically and diachronically, as depicted in Table 1. It will be seen that the case study occupies one of three possible cells. Type I case studies examine variation in a single unit over time, thus preserving the primary unit of analysis.
Other case studies break down this primary unit into subunits, which are then subjected to covariational analysis—either synchronically (type II) or synchronically and diachronically (type III). These are the three logically conceivable approaches to the intensive study of a single unit where that unit is viewed as an instance of some broader phenomenon. Consequently, when one refers to the case study method one is in fact referring to three possible methods, each with a different menu of covariational evidence.
The bottom half of Table 1 lays out various acrossunit research designs (where some important element of the empirical analysis involves comparisons across units). Here I have listed the methods most commonly identi? ed with these research designs. Across-unit analysis without any explicit temporal component (d) is usually classi? ed as “cross-sectional” (even though a temporal component is usually simulated with independent variables that are assumed to precede the dependent variable under investigation). When a temporal component is included we often refer to the analysis as “time–series cross-sectional” (TSCS) or pooled time– series (e).
When one examines variation across- and within units in the same research design one is said to be employing a “hierarchical” model (f). Finally, when all forms of covariation are enlisted in a single research design the resulting method is described as “hierarchical time–series” (if quantitative) or “comparativehistorical” (if qualitative) (g). Of all cross-unit research 3 Note that covariation (or correlation) refers to the mutual relationship between X and Y; variation, to the behavior of a single variable. These words are often used interchangeably.
Hume’s word for this was constant conjunction, and others have been employed as well. I should clarify that although the empirical component of a causal argument is covariational in nature, successful causal arguments depend upon more than just covariation. Among other things, a convincing causal account must identify a causal mechanism (see below). designs the case study is probably closest to the latter, where levels of analysis move up and down more or less simultaneously and where a small number of units are subjected to intensive study.
Indeed, the comparativehistorical study may be looked upon as a series of case studies combined with explicit cross-unit analysis (Mahoney and Rueschemeyer 2003). Having placed these standard cross-unit research designs within a covariational typology one must also take note that each of these methods might also be employed as a case study. A case study may employ crosssectional, TSCS, hierarchical, hierarchical time-series, and perhaps even comparative-historical models. It all depends upon the proposition in question.
Speci? cally, it is the purposes to which these analyses are put, and hence the de?nition of a unit, that determines whether or not they are appropriately referred to as case studies. This will become clearer as we proceed. The N Question I have argued that what distinguishes the case study method from all other methods is its reliance on covariation demonstrated by a single unit and its attempt, at the same time, to illuminate features of a broader set of units. It follows from this that the number of cases (N) employed by a case study may be either small or large and, consequently, may be evaluated in a qualitative or quantitative fashion.
4 To see why this must be so let us consider how a case study of a single event—say, the French Revolution— works. Intuitively, such a study provides an N of one (France). If one were to broaden the analysis to include a second revolution (e. g. , the American Revolution), it would be common to describe the study as comprising two cases. Yet, as I have argued preliminarily, this is a gross distortion of what is really going on. It would be more correct to describe such a study as comprising two units, rather than two cases, for a case study of a single event generally examines that event over time.
France is observed before, during, and after the event to see what changed and what remained the same after this cataclysmic event. These patterns of covariation offer the empirical clues one needs to reach conclusions about causation. They also create multiple cases out of that individual unit. N = 2, at the very least (e. g. , before and after a revolution), in a case study of type I. 4 This section explains and elaborates on a theme ? rst articulated by Campbell (1975) 1988, itself a revision of Campbell’s earlier perspective (Campbell and Stanley 1963).
343 What Is a Case Study? May 2004 If, instead, there is no temporal variation—if, for example, the French Revolution is examined at a single point in time—then the object of investigation will be covariational patterns within that unit, a case study of type II. Within-unit cases consist of all cases that lie at a lower level of analysis relative to the inference under investigation. If the primary unit of analysis is the nationstate, then within-unit cases might be constructed from provinces, localities, groups, or individuals.
The possibilities for within-unit analysis are, in principle, in? nite. Indeed, within-unit N often swamps across-unit N, particularly where individuals comprise the relevant within-unit case. A single national survey will produce a larger sample than any conceivable cross-country analysis. Thus, in many circumstances case studies of type II comprise a larger N than cross-sectional analyses or TSCS analyses. Evidently, if a case study combines both temporal and within-unit variation, as in case studies of type III, then its potential N increases accordingly.
This is probably the most common genre of case study analysis. These covariational facts hold true regardless of whether the method is experimental or nonexperimental. It is also true of counterfactual reasoning, which typically consists of four cases—the actual (as it happened) before and after cases and the before and after cases as reconstructed through counterfactual reasoning (i. e. , with an imagined intervention). In short, the case study does not preclude high-N; it simply precludes across-unit N (by de? nition).
What, then, of the classic N = 1 research design, which haunts the imaginations of social scientists everywhere? This hypothetical research design occupies the empty cell in Table 1. Its cell is empty because it represents a research design that is not logically feasible.
A single unit observed at a single point in time without the addition of within-unit cases offers no evidence whatsoever of a causal proposition. In trying to intuit a causal relationship from this snapshot—a single case without within-unit covariation—we would be engaging in a truly random operation, since an in?nite number of lines might be drawn through that one data point.
Ambiguities–Necessary and Unnecessary The effort in this section has been to clarify what it means to conduct a case study. I have argued that a case study is most usefully de? ned as the intensive study of a single unit wherever the aim is to shed light on a question pertaining to a broader class of units. Although this de? nitional exercise does not settle all the ambiguities besetting the case study research design, it does provide a way of understanding ambiguities that remain. Six issues deserve emphasis.
The ? rst ambiguity concerns the problem of distinguishing different types of covariational evidence. We have pointed out that case studies may observe a single unit through time (type I), synchronic within-unit variance (type II), or synchronic and diachronic withinunit variance (type III). Notice that types II and III, but not type I, involve a change in level of analysis, since cases are drawn from phenomena within the primary unit (as de? ned by the proposition of interest). Thus, some case studies—but not all—involve a change in the primary unit of analysis.
To complicate matters further, case studies often combine observations of the primary unit over time (type I) with synchronic and diachronic observations of within-unit covariation (types II and III). Many case studies are thus hybrids of all three research designs. A ? nal complication is introduced by the fact that it is often dif? cult to ? gure out which sort of covariational evidence is being mobilized at a particular juncture. The dif? culty owes something to the complexities of within-unit analysis. Although the primary unit of analysis is usually clear, within-unit cases are often multiple and ambiguous.
A second source of ambiguity concerns the blurry line between a unit that is intensively studied—the case study—and other adjacent units that may be brought into the analysis in a less structured manner. Recall that because a case study refers to a set of units broader than the one immediately under study, a writer must have some knowledge of these additional units (a) to choose a unit for special treatment and (b) identify plausible causal hypotheses. Case studies are not immaculately conceived; additional units always loom in the background.
To speak of a case study at all it is helpful to introduce a distinction between formal and informal units. The formal unit is the unit chosen for intensive analysis— the person, group, organization, county, region, country, or other bounded phenomenon of which the writer has in-depth knowledge. Informal units consist of all other units that are brought into the analysis in a peripheral way, typically in an introductory or concluding chapter. Often, these informal units are studied only through secondary literature; they are always more super? cially surveyed than the formal unit under study.
Sometimes, the status of informal units is left implicit. This may be warranted in circumstances where the relevant comparison or contrast between the formal unit and other units is obvious or generally accepted. In any case, the distinction between a formal and an informal unit is always a matter of degrees. The more equality of treatment granted to peripheral units, the more a study leans toward a cross-unit style of analysis. The greater the predominance of a single unit, the more it merits the appellation case study. A third ambiguity occurs whenever a single work combines single-unit and across-unit analysis in a formal manner.
This would be true of comparativehistorical work as well as any work in which an intensively studied unit is “nested” within a broader research design (Coppedge 2002; Lieberman 2003). Indeed, the only thing that distinguishes the single-unit study from a sample (which is of course also designed to elucidate the features of some larger phenomenon) is that the latter is generally understood as composed of more than one unit. Case studies, like samples, seek to represent, in all ways relevant to the proposition at hand, a population of cases.
A series of case studies might therefore be referred to as a sample; it is a matter of 344 American Political Science Review Vol. 98, No. 2 emphasis and of degree. The more case studies one has, the less intensively each one is studied, and the more con? dent one is in their representativeness (of some broader population), the more likely one is to describe them as a sample rather than a series of case studies. A fourth ambiguity af? icting case studies is that such works generally partake of two empirical worlds. They are both studies tout court and case studies of something more general.
As a study, the population is restricted to the unit under investigation. As a case study, the population includes adjacent units—perhaps quite a large number of them. This tension is evident in Graham Allison’s (1971) renowned work, whose subtitle, Explaining the Cuban Missile Crisis, invokes a narrow topic, whereas the title, Essence of Decision, suggests a much larger topic (government decision-making). To complicate matters further, different propositions within the same work commonly apply to different populations. Some may be restricted to the unit under study, whereas others have a wider ambit.
This is clearly the case in Allison’s study and is noted explicitly in the introduction. To complicate matters further, the status of a work may change as it is digested and appropriated by a community of scholars. “Meta-analyses” are systematic attempts to integrate the results of individual studies into a single quantitative analysis, pooling individual cases drawn from each study into a single dataset (with various weightings and restrictions). The ubiquitous “literature review” often aims at the same objective, albeit in a less synoptic way.
Both statistical meta-analyses and narrative literature reviews assimilate a series of studies, treating each of them as case studies in some larger project—whether or not this was the intention of the original authors. A ? nal ambiguity concerns the sort of argument that a case study is intended to prove or demonstrate. One species of case study examines a loosely de? ned general topic—war, revolution, gender relations—in a particular setting but offers no speci? c proposition that might be applied across a larger set of units. E. P. Thompson’s The Making of the English Working Class (1963) is usually construed as a case study of class formation.
This suggests a very general purview, perhaps applicable to all countries in the modern era. Yet Thompson does not proffer a theory of class formation, aside from the rather fuzzy notion of a working class participating in its own development. Thus, his work is probably correctly understood as a study of how a more general phenomenon occurred in one country setting. Virtually any intensive study of a relatively bounded topic quali? es as a case study in this minimal sense, so long as it can be linked with some larger topic via a key word (e. g. , class formation).
Indeed, the narrowest terrains sometimes claim the broadest extensions. Studies of a war are studies of war, studies of a farming community are studies of farming communities everywhere, studies of individuals are studies of humanity, and so forth. A very different style of argumentation informs Benjamin Reilly’s (2001) study of the role of electoral systems in ethnically divided societies. Reilly argues, on the basis of several case studies, that single–transferable vote (STV) electoral systems have a moderating effect on group con? ict relative to ?rst-past-the-post (FPP) electoral systems.
Here is a good example of a case study that is more than simply suggestive (for other examples see Eaton 2003, Elman 1997, Lijphart 1968, and Stratmann and Baur 2002). For present purposes, what is signi? cant is that both styles of argumentation— the suggestive and the falsi? able—are legitimately referred to as case studies. Evidently, they have very different methodological implications. But these implications should not be confused with the case study format, which can be implemented in interpretivist as well as positivist modes.
Having ?agged these six ambiguities of the case study, the question is begged: Are they necessary? Are they intrinsic to the research design, or might they be avoided? In many instances, ambiguities can be removed simply by more careful attention to the task of speci? cation (Gerring 2001, 90–99). Writers should be clear about which propositions are intended to describe the unit under study and which are intended to apply to a broader set of units. Regrettably, many studies focused on some element of politics in the United States frame their analysis as a study of politics—by implication, politics in general (everywhere and always).
One is left to wonder whether the study pertains only to American politics, to all contemporary polities, or, in varying degrees, to both. Indeed, the slippage between study and case study accounts for much of the confusion that we encounter when reading single-unit analyses. To the extent that propositions—and their attendant cases, units, and populations—are stated clearly and explicitly, the author avoids confusion and the work attains a higher degree of falsi? ability. This may involve some sacri? ce in narrative ? ow, but it is rightly regarded as the entry price of social science.
However, it hardly seems plausible that the six ambiguities noted above arise solely from the sloppy or unduly belletristic habits of case study practitioners. Indeed, a certain degree of ambiguity is inherent in the enterprise of the case study. This pertains, most of all, to the study/case study distinction. It would be dif? cult to write a study of a single unit that does not also function as a case study, and vice versa, for reasons already explored. Indeed, it may be dif? cult to neatly separate the study and case study components of a work (e. g. , into different chapters or differently labeled propositions).
The reason for this structural ambiguity is that the utility of the single-unit study rests partly on its double functions. One wishes to know both what is particular to that unit and what is general about it. It should be kept in mind that case studies often tackle subjects about which little is previously known or about which existing knowledge is fundamentally ? awed.
The case study typically presents original research of some sort. Indeed, it is the opportunity to study a single unit in great depth that constitutes one of the primary virtues of the case study method (see below). If a writer were to restrict herself only to 345 What Is a Case Study? May 2004 TABLE 2. Af? nities Single-Unit Versus Cross-Unit Research Designs: Tradeoffs and Af? nity 1.
Type of inference 2. Scope of proposition 3. Unit homogeneity 4. Causal insight 5. Causal relationship 6. Strategy of research 7. Useful variance 8. Ontology (a) (b) (a) (b) (c) (a) (b) (a) (b) (a) (b) (a) (b) (a) (b) Descriptive Causal Depth Breadth Boundedness Case comparability (internal) Representativeness (external) Causal mechanisms Causal effect Invariant Probabilistic Exploratory (theory generation) Con? rmatory (theory testing) For only a single unit For many units.
Case Study + + + + + + + Cross-Unit Study + + + + + + + + Indeterminate elements of the unit that were generalizable (i. e. , if she rigorously maintains the “case study” mode of analysis), a reader might justi? ably complain. Such rigor would clarify the population of the primary inference, but it would also constitute a considerable waste of scholarly resources. Imagine a study of economic growth that focuses on Mauritius as a case study yet refuses to engage causal questions unless they are clearly applicable to other countries (since this is a case study of a more general phenomenon, growth).
No mention of factors speci? c to the Mauritian case is allowable; all proper nouns are converted into common nouns (Przeworski and Teune 1970). Such a study seems unduly narrow; its conclusions may mislead. Indeed, it is often dif? cult to tell which of the many features of a given unit are typical of a larger set of units (and hence fodder for generalizable inferences) and which are particular to the unit under study. The appropriate response to such ambiguity is for the writer to report all facts and hypotheses that might be relevant— in short, to overreport. Much of the detail pro.
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