By Kishore K Das and Dibyojyoti Bhattacharjee
The identify «101 Graphical Techniques», itself exhibits the very goal of the ebook. info visualization or graphical illustration of Statistical information is now an rising subfield of information. notwithstanding quite a few graphical suggestions existed in statist!cal literature yet a few quite common graphical innovations are came upon to duplicate themselves in just about all books and journals. yet with the advances within the box of know-how using photographs has elevated again and again. this day, graphical equipment play a huge position in all points of statistical investigation-it starts off with explanatory plots, helps a number of levels of research and is helping within the ultimate communique and reveal of effects. nowadays we see huge use of images in print media, tv information, activities assurance, commercial and so on. And this offers us an idea concerning the improvement of statistical images. lots of the contemporary types of statistical software program are actually generating high-resolution selfexplanatory pix and is including variety of extra graphs in each fresh model in their product. in spite of the fact that, the software program programs don't supply enough textual content to help the aim and interpretation of the rather much less universal images and this in flip limit their use. Social scientists can now get their information analyzed by utilizing graphical instruments which are convenient and more straightforward in comparison to different statistical equipment. yet absence of right textual content has hindered the advance of photographs and there use is specific even if software program is on the market for generating the graphs. The graphical concepts, if used can decrease loads of calculations that's concerned with different statistical suggestions in attaining to a end. a few facts analyst and examine employees are looking for a textual content which could act as a torch bearer on the planet of statistical pics. quite a few universities of Europe and united states have began to increase really good classes on «Data Visualization» or «Statistical Graphics». the fashion is quickly going to go into diversified components of the globe and this booklet will be thought of a convenient fabric for «Statistical Graphics». The publication contains of 10 I statistical plots that may be used for research, show and comparability of knowledge. information units are supplied with many of the plots and suitable calculation if any also are proven. The variables thought of alongside the axes are highlighted and the translation of the graph can also be mentioned. The makes use of of every of the graphical instrument are forwarded in addition to a few comparable statistical/graphical instruments. * broad element clever dialogue approximately many identified and unknown graphical instruments * dwell info set of achieve plot * comparable statistical device for every plot * is helping the reader to settle on applicable plot for his/her facts * Illustrations of train graphical device with all suitable add-ons
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0 [J Source: Economic Survey, 2000-01. Box Plot for Index Number of Industrial Production 220 I 200 ························_·1""·····················_··t-···············--·-·t············· ............. i i .... +........................... 1997-98 1998-98 Non-Outlier Max Non Outlier Min o Median; 75% 25% 1999-2000 2000-2001 Fig. 1. 1 From the plot we can say that the indices of 2000-01 has the maximum scattering, the same year also shows considerable shift in the median compared to the other years.
Disadvantage (a) The plot calls for a lot of computation. The computations increases as the number of observations increases in the data set. (b) Statistical software does not in general provide the option of drawing the plot. 6. Related Techniques (a) Auto Correlation Plot, and (11) Auto Covariance. 1. Description of the Plot The bar chart or bar diagram consists of group of equally spaced rectangular bars, one for each category (or class) fo given statistical data. The bars starting from a common base line, have equal width but their lengths are proporitonal to the values of statistical data that they represent.
5. Related Techniques (a) Pic Diagram. (/J) Multiple Bar Diagram, (e) Sub-divided Bar Diagram, (d) Histogram, and (e) lmpuise Chart. a Bar Chart (Multiple) I 19 • BAR CHART (MULTIPLE) 9. t. Description of the Plot The multiple bar chart or diagratn is developed fi'om simple bar diagram (See Plot 9). Here we have two or more sets ofmHTIhical information under various categories. Thus when the data has several categories whe're each categories have a multiple number of sub-categories common in each ofthese categories, then we can use the multiple bar diagram.
101 Graphical Techniques by Kishore K Das and Dibyojyoti Bhattacharjee