Tiêu đề 11. CONSTRUCTION AND LABELING OF GRAPHS.pdf ✅

PHARMD GURU Page 1 INTRODUCTION: The diagrams and plots that we will be concerned with in our discussion of statistical methods can be placed broadly into two categories: 1. Descriptive plots are those whose purpose is to transmit information. These include diagrams describing data distributions such as histograms and cumulative distribution plots (see sect. 1.2.3). Bar charts and pie charts are examples of popular modes of communicating survey data or product comparisons. 2. Plots that describe relationships between variables usually show an underlying, but unknown analytic relationship between the variables that we wish to describe and understand. These relationships can range from relatively simple to very complex, and may involve only two variables or many variables. One of the simplest relationships, but probably the one with greatest practical application, is the straight-line relationship between two variables, as shown in the Beer’s law plot in Figure 2.1. When analyzing and depicting data that involve relationships, we are often presented with data in pairs (X, Y pairs). In Figure 2.1, the optical density Y and the concentration X are the data pairs. When considering the relationship of two variables, X and Y, one variable can often be considered the response variable, which is dependent on the selection of the second or causal variable. The response variable Y (optical density in our example) is known as the dependent variable. The value of Y depends on the value of the independent variable, X (drug concentration). Thus, in the example in Figure 2.1, we think of the value of optical density as being dependent on the concentration of drug. CONSTRUCTION AND LABELING OF GRAPHS
PHARMD GURU Page 2 CONSTRUCTION AND LABELING OF GRAPHS:  Proper construction and labeling of graphs are crucial elements in graphical data representation.  The design and actual construction of graphs are not in themselves difficult.  The preparation of a good graph, however, requires careful thought and competent technical skills.  One needs not only a knowledge of statistical principles, but also, in particular, computer and drafting competency.  There are no firm rules for preparing good graphical presentations.  Mostly, we rely on experience and a few guidelines. Both books and research papers have addressed the need for a more scientific guide to optimal graphics that, after all, is measured by how well the graph communicates the intended messages(s) to the individuals who are intended to read and interpret the graphs. Still, no rules will cover all situations.  One must be clear that no matter how well a graph or chart is conceived, if the draftsmanship and execution is poor, the graph will fail to achieve its purpose.  A “good” graph or chart should be as simple as possible, yet clearly transmit its intended message. Superfluous notation, confusing lines or curves, and inappropriate draftsmanship (lettering, etc.) that can distract the reader are signs of a poorly constructed graph.  Here, are the few examples to illustrate the recommendations for good graphic presentation as well as examples of graphs that are not prepared well or fail to illustrate the facts fairly. EXAMPLE:  Figure 2.3 shows the results of a clinical study that was designed to compare an active drug to a placebo for the treatment of hypertension. This graph was constructed from the X, Y pairs, time and blood pressure, respectively.  Each point on the graph (+ , ) is the average blood pressure for either drug or placebo at some point in time subsequent to the initiation of the study.  Proper construction and labeling of the typical rectilinear graph should include the following considerations:
PHARMD GURU Page 3 1. A title should be given. The title should be brief and to the point, enabling the reader to understand the purpose of the graph without having to resort to reading the text. The title can be placed below or above the graph as in Figure 2.3. 2. The axes should be clearly delineated and labeled. In general, the zero (0) points of both axes should be clearly indicated. The ordinate (the Y axis) is usually labeled with the description parallel to the Y axis. Both the ordinate and abscissa (X axis) should be each appropriately labeled and subdivided in units of equal width (of course, the X and Y axes almost always have different subdivisions). In the example in Figure 2.3, note the units of mm Hg and weeks for the ordinate and abscissa, respectively. Grid lines may be added [Fig. 2.4(E)] but, if used, should be kept to a minimum, not be prominent and should not interfere with the interpretation of the figure. 3. The numerical values assigned to the axes should be appropriately spaced so as to nicely cover the extent of the graph. This can easily be accomplished by trial and error and a little manipulation. The scales and proportions should be constructed to present a fair picture of the results and should not be exaggerated so to prejudice the interpretation. Sometimes, it may be necessary to skip or omit some of the data to achieve this objective. In these cases, the use of a “broken line” is recommended to clearly indicate the range of data not included in the graph (Fig. 2.4).
PHARMD GURU Page 4 4. If appropriate, a key explaining the symbols used in the graph should be used. For example, at the bottom of Figure 2.3, the key defines as the symbol for placebo and + for drug. In many cases, labeling the curves directly on the graph (Fig. 2.4) results in more clarity.