By Dr. Sigbert Klinke (auth.)

Since the start of the seventies machine is offered to exploit programmable pcs for numerous projects. throughout the nineties the has built from the large major frames to non-public workstations. these days it isn't in simple terms the that's even more strong, yet workstations can do even more paintings than a first-rate body, in comparison to the seventies. In parallel we discover a specialization within the software program. Languages like COBOL for company­ oriented programming or Fortran for clinical computing simply marked the start. The advent of private pcs within the eighties gave new impulses for even additional improvement, already in the beginning of the seven­ ties a few distinct languages like SAS or SPSS have been to be had for statisticians. Now that non-public desktops became highly regarded the variety of professional­ grams begin to explode. at the present time we are going to discover a wide array of courses for nearly any statistical function (Koch & Haag 1995).

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The plot deviates from a standard normal distribution. 33. Parallel coordinate plot with line densities of the two gaussian random variables with mean zero and the covariance matrix being the unit matrix. (z,p) from the formula V(p) = (1 - p)Xl + pX2 for a two dimensional dataset. 33. Instead of 3D-surface plots contour plots and image plots can be used. 10 Basic Properties for Graphical Windows In the preceeding sections we have examined a lot of graphics which are used in statistical computing.

Today's research has been successful in replacing the information we get through our eyes. The hope is that we can represent (hierarchical) statistical objects by graphics. The virtual space of our objects should lead to an easier manipulation of the objects and an easier recognition of relations between the objects. 2 Exploratory Statistical Techniques Summary The first step is to analyze the statistical graphics in use, so we examine the descriptive statistics. Next is the boxplot, the Q-Q plot, the histogram, the regressogram, the barchart, the dotchart, the piechart, the 2D-scatterplot, the 2D-contour plot, the scatterplot matrix, the 3D-scatterplot, the 3D-contour plot, the Chernoff faces and the parallel coordinate plot.

000 D M. 3 Other Views Of course we also need other bivariate plots than scatterplots. For example it can be difficult to overview a density function depending on two random variables which can be plotted in a 3D-scatterplot. 19. (X,Y)=Ci i=1,2, ... g. seeing the global maximum. Another possibility are image plots. 19. Scatterplot of the variables loglO(F A) and loglO(F P) of the whole Berlin flat data (n 14968). 01. A further investigation would show that the peeks we see in the contour plot represent a certain number of rooms.

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