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  • Configurable JCM Applets
    no applet This example is for the SimpleGraph applet The first line specifes the applet class file SimpleGraph class that is to be executed and the size of the applet on the page width 300 pixels and height 300 pixels It also specifies that the class file and any other class files that it references are to be found in the file jcm1 0 config jar which is in the same directory as the Web page If you want to use the configurable JCM applets on your own web pages you should download the file jcm1 0 config jar You don t necessarily have to put it in the same directory as the web page You can put it in a different directory and use a relative path to the file For example archive nbsp jcm1 0 config jar says that the jar file is in the parent directory of the directory that contains the Web page This can be useful if you have several Web pages in different directories you will still only need the one jar file This can be more efficient for users of your pages since a Web browser can just download the file once even if the user visits several Web pages that use the file The sample applet tag defines several params Each param is defined in a param tag which gives its name and value To learn about the available param names and their meanings see the pages for the individual applets and the list of common params on the page Generic params html Expressions in JCM All the applets work with expressions such as x 3 or sqrt k t Expressions can use the operators and where both and indicate exponentiation and they can use the mathematical constants pi and e They

    Original URL path: http://math.hws.edu/javamath/config_applets/index.html (2016-02-07)
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  • Basic JCM Applets
    above pages along with the applets In case you want to download the source code files here is a link that you can use to browse the source code directly Basic JCM Applets source code You should also take a look at the configurable JCM applets which are much more versitile than the basic applets The basic applets were written largely as examples of programming using JCM components Expressions in

    Original URL path: http://math.hws.edu/javamath/basic_applets/index.html (2016-02-07)
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  • Java Components for Math -- Programming Info
    details click here Package edu hws jcm awt The edu hws edu awt package provides classes for building the Graphical User Interface of a mathematical applet or program Many of these classes are subclasses of Java s AWT Abstract Windowing Toolkit components Some of the classes correspond to mathematical objects An ExpressionInput is an input box where the user can type in a mathematical expression Similarly a VariableInput can be used to enter the value of a variable A VariableSlider lets the user set the value of a variable in another way by adjusting a slider actually an object belonging to the AWT s Scrollbar class A DisplayLabel is a Label that can display the values of one or more Value objects embedded in a string of text A DataTableInput makes it possible for the user to input numbers in multiple rows and columns In a mathematical applet something has to happen when the user enters a new value for a variable or expression Other objects such as graphs or value displays have to be updated to reflect the change In the JCM the updates are done by a Controller object A Controller works with objects of three types InputObject which represents objects that can change requiring other updates Computable which represents object that might have to be updated and Tie which makes it possible to synchronize two objects so that they will always have the same value Objects of these three types must be added to a Controller if they are to function properly and in addition each InputObject must be set to notify the Controller when it changes in order for the change to have any effect on other objects The JCMPanel class makes it possible to avoid much of the work of setting up Controllers JCMPanel is a subclass of Java s Panel class so it can contain other graphical user interface components including other JCMPanels If an interface is built entirely of JCMPanels then most of the Controller setup is done automatically and anther aspect of the setup can be accomplished simply by calling the gatherInputs method in the main JCMPanel For more details click here Package edu hws jcm draw The edu hws jcm draw package makes it possible to display two dimensional graphical objects such as graphs of functions parametric curves and vector fields The core class in the package is DisplayCanvas which represents an area where such objects can be displayed A CoordinateRect is an object that lays out horizontal and vertical coordinates on a DisplayCanvas or on a rectangular area within a DisplayCanvas Graphical objects are actually associated with CoordinateRects A LimitControlPanel is a graphical user interface component that can be placed elsewhere in an applet outside the DisplayCanvas to allow the user to control the range of horizontal and vertical coordinates on a CoordinateRect Objects that can be added to CoordinateRects are subclasses of the abstract class Drawable These include for example Axes representing pair of horizontal and vertical coordinate axes

    Original URL path: http://math.hws.edu/javamath/proginfo/index.html (2016-02-07)
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  • Generated Documentation (Untitled)
    Alert This document is designed to be viewed using the frames feature If you see this message you are using a non frame capable web client Link to Non frame

    Original URL path: http://math.hws.edu/javamath/javadoc/index.html (2016-02-07)
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  • Index of /javamath/jcm1-source
    2012 04 11 14 12 19K Parametric java 2012 04 11 14 12 17K README html 2012 04 11 14 12 1 0K RiemannSums java 2012 04 11 14 12 13K ScatterPlotApplet java 2012 04 11 14 12 15K SecantTangent java 2012 04 11 14 12 13K SimpleGraph java 2012 04 11 14 12 13K edu 2012 04 11 14 12 About these source files This folder contains the source

    Original URL path: http://math.hws.edu/javamath/jcm1-source/ (2016-02-07)
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  • MATH 130: Calculus I
    2 and 4 4 We will skip Section 4 3 Implicit Differentiation This means that we will also have to skip over a few references to implicit differentiation later in the book Some suggested problems from these sections Section 4 1 1 3 9 11 17 19 35 Section 4 2 1 5 11 13 17 23 29 55 Section 4 4 3 7 13 21 27 29 37 43 45 There is no lab report due this week but there is a short WebWork homework set due by the beginning of lab on Thursday Eighth Week March 19 21 and 23 There is a test this week on Friday March 23 It will cover Chapter 2 sections 3 4 and 5 Chapter 3 sections 1 through 5 and Labs 4 through 7 Information about this test can be found on the information sheet for the test The next WebWork Homework is due on Thursday We will finish Chapter 3 this week We might start in on Chapter 4 but any material that we cover from Chapter 4 will not be on the test Here are some suggested problems from Section 3 5 Section 3 5 1 5 7 15 19 21 23 27 29 31 39 45 57 63 65 Sixth and Seventh Weeks February 26 to March 9 We will continue working through Chapter 3 which introduces derivative functions and covers most of the essential material on finding derivatives of formulas By Friday March 9 we should be doing Section 3 5 Note that we will not cover Section 3 6 March 10 is the beginning of Spring break Please remember that there is a test coming up on the Friday after Spring break I expect the test to cover material through Section 3 5 The next WebWork homework 5 is available as of Sunday March 4 and is due on the Thursday after break Here are the suggested practice problems for Sections 3 2 3 3 and 3 4 Section 3 2 1 5 7 9 21 23 25 35 Section 3 3 3 5 11 17 23 27 37 43 57 61 77 Section 3 4 1 3 7 11 13 17 33 35 Fifth Week February 19 21 and 23 This week we will finish Chapter 2 and begin Chapter 3 You should read up to Section 3 2 From section 2 5 you only need to know the limit of sin x x as x approaches 0 the limit of 1 cos x x as x approaches 0 and how to use these limits to compute other limits involving trigonometric functions Lab Report 4 is due on Wednesday There is no WebWork assignment due this week but there will be a new WebWork homework set available on Thursday or sooner Here are some suggested practice problems Section 2 4 1 3 7 9 13 15 23 Section 2 5 17 23 27 29 35 37 51 Section 3 1 1 5 7 11 15

    Original URL path: http://math.hws.edu/eck/math130_s01/ (2016-02-07)
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  • Chi Square Statistics
    4 3 357 7 779 9 488 11 668 13 277 18 465 5 4 351 9 236 11 070 13 388 15 086 20 517 To make the chi square calculations a bit easier plug your observed and expected values into the following applet Click on the cell and then enter the value Click the compute button on the lower right corner to see the chi square value printed in the lower left hand coner Chi Square Goodness of Fit One Sample Test This test allows us to compae a collection of categorical data with some theoretical expected distribution This test is often used in genetics to compare the results of a cross with the theoretical distribution based on genetic theory Suppose you preformed a simpe monohybrid cross between two individuals that were heterozygous for the trait of interest Aa x Aa The results of your cross are shown in Table 4 Table 4 Results of a monohybrid coss between two heterozygotes for the a gene A a Totals A 10 42 52 a 33 15 48 Totals 43 57 100 The penotypic ratio 85 of the A type and 15 of the a type homozygous recessive In a monohybrid cross between two heterozygotes however we would have predicted a 3 1 ratio of phenotypes In other words we would have expected to get 75 A type and 25 a type Are or resuls different Calculate the chi square statistic x 2 by completing the following steps For each observed number in the table subtract the corresponding expected number O E Square the difference O E 2 Divide the squares obtained for each cell in the table by the expected number for that cell O E 2 E Sum all the values for O E 2 E This is the chi square statistic For our example the calculation would be Observed Expected O E O E 2 O E 2 E A type 85 75 10 100 1 33 a type 15 25 10 100 4 0 Total 100 100 5 33 x 2 5 33 We now have our chi square statistic x 2 5 33 our predetermined alpha level of significalnce 0 05 and our degrees of freedom df 1 Entering the Chi square distribution table with 1 degree of freedom and reading along the row we find our value of x 2 5 33 lies between 3 841 and 5 412 The corresponding probability is 0 05 P 0 02 This is smaller than the conventionally accepted significance level of 0 05 or 5 so the null hypothesis that the two distributions are the same is rejected In other words when the computed x 2 statistic exceeds the critical value in the table for a 0 05 probability level then we can reject the null hypothesis of equal distributions Since our x 2 statistic 5 33 exceeded the critical value for 0 05 probability level 3 841 we can reject the null hypothesis that the observed

    Original URL path: http://math.hws.edu/javamath/ryan/ChiSquare.html (2016-02-07)
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  • Diversity Index
    D 25 1 Diversity Applet To use this applet click in the white box in the table at the left For each species in the sample enter the number of individuals observed in the cell in the table This number should be an integer larger than 0 because you can not have 2 or 0 5 species Press the return or enter key on your keyboard to go to the next cell in the table When all of the dat has been added to the table click the Compute button and the Shannon Index values will appear on the right Click the Clear Data button to clear all the entries from the table Note Some versions of Netscape do not support Java 1 1 If you are using one of these browsers you will not see the applet above Notice what happened to the values of H 1 and H 1 max When all the organisms are in the same proportion in the sample the H 1 H 1 max In the second pond sample where the proportions of species A is much higher than that for any other species the H 1 value is much less than the H 1 max for that sample In short what this indicates is that the diversity of pond 1 is much higher than pond 2 even though both have the same number of species and individuals To see why this is so read the sections below on how these diversity measures are calculated Diversity Measures Biologists use the mathematics of information theory to make precise calculations about entities that we will call first order diversity H 1 and divergence from equiprobability D 1 Definition 1 Assume that there are n possible categories in a data set and that their proportions are p

    Original URL path: http://math.hws.edu/javamath/ryan/DiversityTest.html (2016-02-07)
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