visual basic 6.0 barcode generator The Entire Stats Class in Java

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The Entire Stats Class
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All of the statistical methods can be assembled into a class called Stats, as shown next. The same file also makes a convenient place to store the RegData and NoModeException classes.
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import java.util.*; import java.text.*; // This class holds the regression analysis data. class RegData { public double a, b; public double cor; public String equation; public RegData(double i, double j, double k, String str) { a = i; b = j; cor = k;
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8: Statistics, Graphing, and Java
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equation = str; } } // This is the exception thrown by mode() class NoModeException extends Exception { public String toString() { return "Set contains no mode."; } } // A general-purpose statistics class. public class Stats { // Return the average of a set of values. public static double mean(double[] vals) { double avg = 0.0; for(int i=0; i < vals.length; i++) avg += vals[i]; avg /= vals.length; return avg; } // Return the median of a set of values. public static double median(double[] vals) { double temp[] = new double[vals.length]; System.arraycopy(vals, 0, temp, 0, vals.length); Arrays.sort(temp); // sort the data // Return the middle value. if((vals.length)%2==0) { // If even number of values, find average. return (temp[temp.length/2] + temp[(temp.length/2)-1]) /2; } else return temp[temp.length/2]; } /* Returns the mode of a set of values. A NoModeException is thrown if no value occurs more frequently than any other.
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If two or more values occur with the same frequency, the first value is returned. */ public static double mode(double[] vals) throws NoModeException { double m, modeVal = 0.0; int count, oldcount = 0; for(int i=0; i < vals.length; i++) { m = vals[i]; count = 0; // Count how many times each value occurs. for(int j=i+1; j < vals.length; j++) if(m == vals[j]) count++; /* If this value occurs more frequently than the previous candidate, save it. */ if(count > oldcount) { modeVal = m; oldcount = count; } } if(oldcount == 0) throw new NoModeException(); else return modeVal; } // Return the standard deviation of a set of values. public static double stdDev(double[] vals) { double std = 0.0; double avg = mean(vals); for(int i=0; i < vals.length; i++) std += (vals[i]-avg) * (vals[i]-avg); std /= vals.length; std = Math.sqrt(std); return std; }
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/* Compute the regression equation and coefficient of correlation for a set of values. The values represent the Y coordinate. The X coordinate is time (i.e., ascending increments of 1). */ public static RegData regress(double[] vals) { double a, b, yAvg, xAvg, temp, temp2, cor; double vals2[] = new double[vals.length]; // Create number format with 2 decimal digits. NumberFormat nf = NumberFormat.getInstance(); nf.setMaximumFractionDigits(2); // Find mean of Y values. yAvg = mean(vals); // Find mean of X component. xAvg = 0.0; for(int i=0; i < vals.length; i++) xAvg += i; xAvg /= vals.length; // Find b. temp = temp2 = 0.0; for(int i=0; i < vals.length; i++) { temp += (vals[i]-yAvg) * (i-xAvg); temp2 += (i-xAvg) * (i-xAvg); } b = temp/temp2; // Find a. a = yAvg - (b*xAvg); // Compute the coefficient of correlation. for(int i=0; i < vals.length; i++) vals2[i] = i+1; cor = temp/vals.length; cor /= stdDev(vals) * stdDev(vals2); return new RegData(a, b, cor, "Y = " + nf.format(a) + " + " + nf.format(b) + " * X"); } }
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Graphing Data
Although statistics are useful by themselves, they don t always give a complete feel for the data. In many cases, it is helpful to see the data displayed in some form of graph. Depicting data in a visual form enables one to spot both correlations and anomalies that might not be immediately apparent simply by reviewing the statistics. A graph also shows at a glance how the data is actually distributed and its variability. Because of the importance of graphs to statistics, three graphing methods are developed here. In addition to displaying data in a visually useful form, the graphing methods provide a secondary benefit: they illustrate several techniques related to Java s AWT and event handling. As you know, the AWT is part of the core Java class library. It provides support for a graphically oriented, window-based environment that is, a graphical user interface (GUI). A GUI-based application interacts with the user by handling events, which include everything from keystrokes, to menu selections, to repaint and resizing requests. In the process of developing the graphing methods, we will be dealing with several side issues relating to the GUI environment. For example, a graph must be dynamically scalable because a user might resize the window that contains it. This chapter develops three types of graphs. The first is a bar graph, the second is a scatter graph, and the third is a scatter graph that includes the regression line. As you will see, much of the code, such as that which scales output, is common to all three.
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