Tukey, J. W. (1977). Exploratory Data Analysis. Reading, MA: Addison-Wesley.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....with attributes having identical names and meaning (Example: Number of Students Enrolled in Second Grade in 2000 01) but different values, because they came from different data sources at different times. 4. 1 Approach and Rationale The case studies employ an exploratory data analysis (EDA) [37] strategy with a strong component of visualization, augmented by consideration of issues involving relational databases. The emphases are on: Metadata Characteristics, including information about the database, its structure, tables, and attributes, as well as missing and incomplete values. ....

J. Tukey. Exploratory Data Analysis. Addison--Wesley, Reading, MA, 1977.

....pixels. This is because PMTs are extremely sensitive. The uncertainty (governed by Poisson statistics) in the knowledge of the detector current at low light levels usually shows up as isolated voxels of high intensity (shot noise) in the image. Shot noise is dealt with by applying a median filter [80] to the image. The median filter is a non linear, lowpass filter which replaces the greyscale value 45 of each voxel v in the digitized image by the median greyscale value of v and its 26 neighbors. This effectively removes shot noise but not real spines which, under typical magnifications ....

J. W. Tukey. Exploratory data analysis. Addison-Wesley, Reading, MA, 1971.

....states. Difficulties here are not unique to modeling with Bayesian networks, but rather are common to most approaches. Although there are no clean solutions, some guidance is offered by decision analysts (e.g. Howard and Matheson, 1983) and (when data are available) statisticians (e.g. Tukey, 1977) In the next phase of Bayesian network construction, we build a directed acyclic graph that encodes assertions of conditional independence. One approach for doing so is based on the following observations. From the chain rule of probability,wehave p(x i jx 1 #: #x i;1 ) 17) Now, for every ....

Tukey, J. (1977). Exploratory Data Analysis. Addison--Wesley. 56

.... Continuous Data Vitorino Ramos CVRM GeoSystems Centre, Technical University of Lisbon, Portugal vitorino.ramos alfa.ist.utl.pt Ajith Abraham Oklahoma State University Tulsa, OK 74106, USA aa cs.okstate.edu Abstract While being it extremely important, many Exploratory Data Analysis (EDA [21]) systems have the inhability to perform classification and visualization in a continuous basis or to self organize new data items into the older ones (evenmore into new labels if necessary) which can be crucial in KDD Knowledge Discovery [10,1] Retrieval and Data Mining Systems [15,10] ....

John Tukey (1977), Exploratory Data Analysis, Addison-Welsey.

....Still, improvement is demonstrated over telemetry. Further, the present limitations lie more in the quality of the reference data (i.e. elevation) than in the algorithm per se. Summary results for all 8 test clips, both telemetry based and final algorithm registration, are shown as Box Plots [17] in Fig. 7. Note that the ordinate scale on the telemetry results is a factor of 10 greater than the final results. A number of overall observations are possible: i) The best telemetrybased registration is worse than the worst case algorithm reg6 10 20 30 40 50 60 26 74 98 146 194 218 266 ....

J. Tukey, Exploratory Data Analysis, Addison-Wesley, Reading, MA, 1977.

....n , and for each x i , there is a value x ij for the ith amino acid index value at the jth position. Thus x i1 through x ik constitutes a profile of the protein in terms of the ith amino acid property index (see Figure 2) Then each raw profile is smoothed by applying the Sliding Window Recognizer [19], which transforms the profile as follows: x # ij = d k= d w j k x j k , where d is the kernel size (16 in our tests) and w is the kernel window (a Gaussian function in our tests) We followed a procedure similar to the method used by Kim et al. 14] We first computed moving window profiles ....

J. L. Tukey. Exploratory data analysis. Addison Wesley, 1977.

....that distinguish different modes of behavior, functional simplification of lowdimensionality relationships, and two waytablessuchascontingency tables. These are just a few simple examples# a sophisticated analysis combines these and many others in the construction of a global picture of the data [Tukey77, Hoaglin83]. We are developing an assistant for intelligent data exploration, aide, to assist human analysts with EDA [StAmant95] Aide takes a script based planning approachtoEDA. Data directed mechanisms extract simple observations and suggestive indications from the data. Scripted combinations of ....

....similar, relying on a measure of group separation, S (K) At each step a decision is made whether to continue or to halt with the model generated so far. An example of an exploratory procedure is the straightening of a bivariate relationship, using Tukey s ladder of transformation [Tukey77]. One begins by splitting the relationship horizontally (along the x axis) into into three partitions. Each partition is reduced to a representative hx# yi coordinate. We use the medians of each partition to determine these points. This gives a three point summary of the data. If these points fall ....

John W. Tukey. Exploratory Data Analysis. Addison-Wesley, 1977. Available at http://eksl-www.cs.umass.edu/eksl.html 5

.... reasons prevent further elaboration on the specific attributes; a standard least squares regression model developed on the same attributes provides a baseline for comparison of the GA obtained results) This data from a customer database was subjected to the normal exploratory data analyses [29] and variable transformation and reduction procedures, 4] in consideration of the final model being developed as a linear combination of attributes. The final data contained six attributes, four continuous and two dummy attributes. All continuous attributes were normalized to zero mean and unit ....

J.W. TUKEY, 1977. Exploratory Data Analysis, Addison Wesley, Reading, MA.

....became clear that the results were primarily artifacts of the regression technique: contradictory bound claims, suchas Omega (x 2:2 )andO(x 1:8 )were easy to obtain by small changes in the regression method. This approachwas abandoned early in this research. The second is based on Tukey s [16] ladder of transformations. This approachalsogives contradictory results depending on whether the transformation is applied to Y or X. ....

J. W. Tukey (1977) Exploratory Data Analysis, Addison-Wesley.

....identify suggestive features of the data, interpret the patterns these features indicate, and generate hypotheses to explain the patterns. Successive steps through the process lead us gradually to a better understanding of underlying structure in the data [11, 6] Exploratory data analysis (EDA) [16] gives us a powerful set of operations for this process: we fit linear and higher order functions to relationships# we compose and transform variables with arithmetic functions# we separate relationships into partitions and clusters# we extract features through statistical summaries. Through the ....

John W. Tukey. Exploratory Data Analysis. Addison-Wesley,1977. 13

....became clear that the results were primarily artifacts of the regression technique: contradictory bound claims, suchas Omega (x 2:2 ) and O(x 1:8 )were easy to obtain by small changes in the regression method. This approachwas abandoned early in this research. The second is based on Tukey s [16] ladder of transformations. This approach also gives contradictory results depending on whether the transformation is applied to Y or X. ....

J. W. Tukey (1977) Exploratory Data Analysis, Addison-Wesley.

....nonlinear filters are poorly understood. Median filtering is one of the most common nonlinear techniques used in signal processing. Among the first to demonstrate the benefits of taking medians of sample data were Borda and Frost [31] and the median filter itself is generally ascribed to Tukey [29]. The properties of the median filter have been studied in quite some depth since these early uses [6, 7, 8, 9, 10] The edge preserving and impulse removing properties of this filter are usually the most desirable features, and although the median filter is not conceptually complex, its ....

Tukey, J. W. Exploratory Data Analysis. Reading, MA: AddisonWesley, 1971.

....and parameter settings of the techniques. The experiences obtained from these experiments can be used for the design and conduction of a more formal and extensive usability analysis. Nevertheless, several interesting observations can be made. Figure 7. 12 shows box and whisker plots [Tuk77] of the task completion times per method and per subject. A box and whisker plot shows a central box from the lower quartile to the upper quartile (i.e. the box covers the center half of the data) the mean completion time (a ) and the median completion time (the horizontal line inside a box) ....

J.W. Tukey. Exploratory Data Analysis. Addison-Wesley, 1977.

....states. Difficulties here are not unique to modeling with Bayesian networks, but rather are common to most approaches. Although there are no clean solutions, some guidance is offered by decision analysts (e.g. Howard and Matheson, 1983) and (when data are available) statisticians (e.g. Tukey, 1977) In the next phase of Bayesian network construction, we build a directed acyclic graph that encodes assertions of conditional independence. One approach for doing so is based on the following observations. From the chain rule of probability, we have p(x) 1 IP(xilx, xi ) 17) Now, for ....

Tukey, J. (1977). Exploratory Data Analysis. Addison-Wesley. 56

....Markov analysis, and lag sequential analysis are being adapted to the needs of video data interpretation [9, 13, 18] The complexity of the interactions that occur in such data is also leading to an emphasis on exploratory, rather than confirmatory, analyses. Exploratory Data Analysis (EDA) [24] is concerned with developing insights about processes through examining the outputs or data that they generate. This exploration is quite different from the directed data collection of hypothesis based (confirmatory) analyses. EDA allows researchers to formulate hypotheses and visualize ....

Tukey, J.W. (1977). Exploratory Data Analysis. Reading, MA: Addison-Wesley.

....comparisons and describes how such hypercubes can be generated by the classification hierarchy described in section 2. In keeping with the nature of HyperSet as an exploratory tool, the kind of analyses outlined here belong to the sphere of exploratory, rather than confirmatory, data analysis [Tukey 77] That is, we are looking for suggestive patterns, not trying to establish certainty values for a specific hypothesis. In general, the domain expert, not the statistician, is best equipped to detect meaningful patterns in data, if only the data are presented clearly, and HyperSet seeks to support ....

J.Tukey, Exploratory Data Analysis. Reading: Addison-Wesley.

....orientation, texture, size, and shape. Viewers do not need to consciously examine a display to notice changes in texture patterns or anomalous line orientations. 2. 3 Exploratory Data Analysis Our approach with the development of the given tools is to provide new exploratory data analysis tools [21, 18]. 2 3 4 2001 04 22 08:40:52 SYS: inetd[189] ftp[28103] from 63.59.18.29 1378 169.226.1.101 var adm messages System 2 3 4 2001 04 22 08:40:52 SUNY: User aallll legged in n ftp28103 frm 1Cust29.tntl.glenn falls.ny.da.u 169.226.1.101 var adm wtmpx System 2 3 4 2001 04 22 08:41:58 SYS: ....

John W. Tukey, Exploratory Data Analysis, Addison-Wesley, 1977.

....meon filtering where eoch pixel is reploced by the meon of o neighborhood. This does remove noise, but olso blurs detoils. Another importont ond well studied olgorithm, is medion filtering. In medion filtering the current pixel volue is reploced with the medion volue of o locol neighborhood, see [Tukey 1976, Norendro 1981, Huong e a . 1979, Gollogher ond Wise 1981] This is noticeobly better with respect to preserving detoil, when the detoil is lorger thon the medion window. It still, however, blurs fine detoil, e.g. corners, thin lines, ropidly vorying texture. To moke these stotisticol ....

J.W. Tukey. Exploratory Data Analysis. Addision-Wesley, Reading, MA, 1976. Chapter 7.

....and, as such, it can easily attain prominent significance. Statistics defines an outlier as a point that does not fit a probability distribution. This approach has the problem with discordance testing for unknown multivariate distribution. Classic data analysis utilizes a concept of depth (Tukey [Tuk77]) and defines an outlier as a point of low depth. It becomes computationally infeasible for d 3. Knorr Ng [KN98] define outliers in terms of a distance and two parameters c, c. A point is an outlier if its cneighborhood contains less than 1 c fraction of whole dataset X. This definition is ....

Tukey, J.W., Exploratory Data Analysis, Addison-Wesley, 1977.

....of 0.11 and the ROC metrics [20, 6] had a standard deviation of 0.0037. Second, these results were obtained using a boosted naYve bayesian classifier; a classification tree induction technique produced analogous results. 8 Related Work Data preprocessing is a standard practice in statistics [28], pattern recognition and data mining [26] Generic data cleansing techniques are well described in [ 10] Grouping of categorical values as it relates to tree induction techniques is discussed in [25] while thresholding of continuous variables is discussed in [8] in [9] information based ....

Tukey, J.W., Exploratory Data Analysis. Addison-Wesley, Reading, MA, 1977. 16

....the same as Problem Solving Methods. Of course, our earlier work only described problem paradigms as data analysis methods, but the idea is clearly more general than that. The problem domMn of exploratory data and pattern analysis contains many general Mgorithms that are applied to specific data [45] [13] 14] 26] and the develop ment was advanced by the abstractions existing in the field. There are many problem paradigms possible for a given analysis problem. They differ in viewpoint, assumptions, requirements, and behavior. Given an analysis question, it is usually possible to get more ....

John W. Tukey, Exploratory Data Analysis, Addison-Wesley (1977)

....is like working in a test kitchen: before one writes down the final version of a recipe, one first tries out possible alternative procedures and evaluates the results. Exploratory results influence confirmatory studies in a cycle of successively more refined exploration and confirmation [2, 5, 6, 12]. We apply two general strategies in exploring data: one generates simplifying descriptions of data, the other extends and refines surface descriptions of data. We simplify data by constructing partial descriptions and models that capture particular characteristics of the data. The descriptions ....

....a lower level of detail. Exploratory strategies generate increasingly detailed, complementary descriptions of data. EDA strategies often takes advantage of intermediate results that suggest further areas of exploration. We can best illustrate the process with a brief example, adapted from Tukey [12]. Consider Figure 1, which plots the population of the U.S. between 1800 and 1950. 150 125 100 75 so 25 25 Figure 1: Population vs Date 5.0 4.5 4.0 3.5 3.0 2.5 2.0 1.5 Figure 2: Log Population vs Date We first notice that population in earlier decades increases at a ....

Tukey, J.W., 1977. Exploratory Data Analysis. Addison-Wesley. 12

No context found.

Tukey, J. W. (1977). Exploratory Data Analysis. Reading, MA: Addison-Wesley.

No context found.

Tukey, J. W. 1977, Exploratory Data Analysis. Reading, Mass.: Addison-Wesley.

No context found.

J. W. Tukey. Exploratory data analysis. Addison-Wesley, 1977.

No context found.

Tukey, J.W. (1977). Exploratory data analysis. Addison-Wesley, Reading, MA.

No context found.

TUKEY, J. W. 1977. Exploratory data analysis. Addison-Wesley, Reading, Massachusetts.

No context found.

J. W. Tukey. Exploratory data analysis. Addison-Wesley, Reading MA, 1977.

No context found.

J. Tukey, Exploratory Data Analysis. Menlo Park, CA: AddisonWesley, 1977.

No context found.

Tukey, J.W. (1977) Exploratory Data Analysis. Addison Wesley, Reading.

No context found.

J. W. Tukey. Exploratory data analysis. Addison-Wesley, 1977.

No context found.

J. W. Tukey. Exploratory data analysis. Addison-Wesley, 1977.

No context found.

J. W. Tukey. Exploratory Data Analysis. Addison Wesley, 1977.

No context found.

J. W. Tukey. Exploratory Data Analysis. Addison Wesley, 1977.

No context found.

J. W. Tukey. Exploratory Data Analysis. Addison Wesley, 1977.

No context found.

J. Tukey,Exploratory Data Analysis,Addison-Wesley, Reading,MA,1adi

No context found.

J. W. Tukey. Exploratory data analysis. Addison-Wesley, 1977.

No context found.

J. W. Tukey. Exploratory Data Analysis. Addison Wesley, 1977.

No context found.

J. Tukey, Exploratory Data Analysis. Menlo Park, CA: AddisonWesley, 1977.

No context found.

J. W. Tukey, Exploratory Data Analysis (Addison--Wesley, Reading, Mass., 1977).

No context found.

Tukey, J.W. (1977). Exploratory data analysis. Addison-Wesley, Reading, MA. 23

No context found.

J. W. Tukey. Exploratory Data Analysis. Addison Wesley, 1977.

No context found.

Tukey, J.W. (1977). Exploratory data analysis. Addison-Wesley, Reading, MA.

No context found.

J.W. Tukey. Exploratory Data Analysis. AddisonWesley, 1977.

No context found.

John W. Tukey. Exploratory Data Analysis. Addison Wesley College, 1997.

No context found.

Tukey, J.W. (1977). Exploratory data analysis. Addison-Wesley, Reading, MA.

No context found.

Tukey, J.W., Exploratory Data Analysis, 1977, Reading, Mass.: Addison Wesley.

No context found.

Tukey, J.W. (1977). Exploratory data analysis. Addison-Wesley, Reading, MA.

No context found.

J. Tukey. Exploratory Data Analysis. Addison Wesley, 1975.

No context found.

Tukey, J.W., 1977. Exploratory Data Analysis. Addison-Wesley.

First 50 documents  Next 50

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC