PKEUmXñB–Hmimetypetext/x-wxmathmlPKEUmXQdBV55 format.txt This file contains a wxMaxima session in the .wxmx format. .wxmx files are .xml-based files contained in a .zip container like .odt or .docx files. After changing their name to end in .zip the .xml and eventual bitmap files inside them can be extracted using any .zip file viewer. The reason why part of a .wxmx file still might still seem to make sense in a ordinary text viewer is that the text portion of .wxmx by default isn't compressed: The text is typically small and compressing it would mean that changing a single character would (with a high probability) change big parts of the whole contents of the compressed .zip archive. Even if version control tools like git and svn that remember all changes that were ever made to a file can handle binary files compression would make the changed part of the file bigger and therefore seriously reduce the efficiency of version control wxMaxima can be downloaded from https://github.com/wxMaxima-developers/wxmaxima. It also is part of the windows installer for maxima (https://wxmaxima-developers.github.io/wxmaxima/). If a .wxmx file is broken but the content.xml portion of the file can still be viewed using an text editor just save the xml's text as "content.xml" and try to open it using a recent version of wxMaxima. If it is valid XML (the XML header is intact, all opened tags are closed again, the text is saved with the text encoding "UTF8 without BOM" and the few special characters XML requires this for are properly escaped) chances are high that wxMaxima will be able to recover all code and text from the XML file. PKEUmX¯‘ëÆ`c`c content.xml Kedvenc Matematikai Kísérleteim Alapok Halmazok és függvények Számok Határérték Differenciálszámítás Integrálszámítás Lineáris algrebra Többváltozós függvények Mérték és valószínűség Mérték Integrál Felületi integrál L^p-terek Valószínűségszámítás Statisztika Minta, statisztika Az empirikus eloszlásfüggvény Hisztogram Becslések Konfidencia-intervallumok Hipotézisvizsgálat Paraméteres próbák Nemparaméteres próbák A χ^2-próba A legkisebb négyzetek módszere Feladat kill(all); (%o0) done load("descriptive")$ ;; Note: Tail−recursive call of BIPART was replaced by iteration.;; Note: Tail−recursive call of BIPART was replaced by iteration. (1) X:[12.15,12.33,10.25,9.80,12.90,12.04,11.45,9.64,11.20, 9.78,10.89,11.22,11.91,10.78,10.04,10.35,11.32,9.18, 11.36,10.40,10.89,11.50,11.26,11.95,9.28,11.11,10.34, 11.12,9.71]; (%o2) [12.15,12.33,10.25,9.8,12.9,12.04,11.45,9.64,11.2,9.78,10.89,11.22,11.91,10.78,10.04,10.35,11.32,9.18,11.36,10.4,10.89,11.5,11.26,11.95,9.28,11.11,10.34,11.12,9.71] smin(X); (%o3) 9.18 smax(X); (%o4) 12.9 FX(x):=''(cdf_empirical(X)); (%o5) FX

x

:=charfun

x>=12.9

+charfun

x>=12.33

+charfun

x>=12.15

+charfun

x>=12.04

+charfun

x>=11.95

+charfun

x>=11.91

+charfun

x>=11.5

+charfun

x>=11.45

+charfun

x>=11.36

+charfun

x>=11.32

+charfun

x>=11.26

+charfun

x>=11.22

+charfun

x>=11.2

+charfun

x>=11.12

+charfun

x>=11.11

+2*charfun

x>=10.89

+charfun

x>=10.78

+charfun

x>=10.4

+charfun

x>=10.35

+charfun

x>=10.34

+charfun

x>=10.25

+charfun

x>=10.04

+charfun

x>=9.8

+charfun

x>=9.78

+charfun

x>=9.71

+charfun

x>=9.64

+charfun

x>=9.28

+charfun

x>=9.18

29
FX(11.11); (%o6) 1529 FX(11.109); (%o7) 1429 plot2d(F(x),[x,8,14])$ plot2d: expression evaluates to non−numeric value everywhere in plotting range.plot2d: nothing to plot. (2) nX:length(X); (%o9) 29 nX^(1/3)/2; (%o10) 29132 float(%), numer; (%o11) 1.536158412842923 quantile(X,1/4); (%o12) 10.25 quantile(X,3/4); (%o13) 11.45 histogram(X,nclasses=[9.05,13.25,7])$ histogram(X); (%o16) [gr2d

bars

]
(3) mX:mean(X); (%o17) 10.90172413793103 (4) var1(X); (%o18) 0.9138647783251231 %^(1/2); (%o19) 0.9559627494443093 (5) load(distrib)$ quantile_normal(.975,0,1); (%o21) 1.385903824349678*2 float(%), numer; (%o22) 1.959963984540054 I:[-%,%]; (%o23) [−1.959963984540054,1.959963984540054] u:(mX-11.2)/1*n^(1/2); (%o24) −0.2982758620689676*n float(%), numer; (%o25) −0.2982758620689676*n0.5 Feladat Y:[10.62,13.10,12.40,9.80,10.31,9.25,10.87,9.93, 9.72,12.34,11.77,13.23,9.20,10.11,11.66,10.79, 11.06,12.71,10.89,11.19,10.93,10.17,11.97,9.14, 11.76,11.60,9.14,10.56,11.57,12.53]; (%o26) [10.62,13.1,12.4,9.8,10.31,9.25,10.87,9.93,9.72,12.34,11.77,13.23,9.2,10.11,11.66,10.79,11.06,12.71,10.89,11.19,10.93,10.17,11.97,9.14,11.76,11.6,9.14,10.56,11.57,12.53] nY:length(Y); (%o27) 30 mY:mean(Y); (%o28) 11.01066666666666 I; (%o29) [−1.959963984540054,1.959963984540054] u:(mX-mY)/(1/29+1.2^2/30)^(1/2); (%o30) −0.3793288400821966 Feladat (1) I; (%o31) [−1.959963984540054,1.959963984540054] u:(mY-11.2)/1.2*nY^(1/2); (%o32) −0.1577777777777796*30 float(%), numer; (%o33) −0.8641844796192724 (2) FY(x):=''(cdf_empirical(Y))$ XY:append(X,Y)$ ε:0.001; (%o36) 0.001 map(lambda([x],x-ε),XY)$ XYε:append(%,XY)$ FXYL:map(FX,XYε)-map(FY,XYε); (%o39) [14145,19145,−17290,1174,14435,9145,18145,−28435,−7145,−5174,−23435,−2145,23870,−3145,−23870,−287,8145,−115,13145,187,−23435,23145,3145,53870,−43435,−73870,−587,−43870,−13435,11870,115,23174,1174,−7290,−19290,−17870,1145,2435,24145,26435,130,−14435,7870,1187,2145,−22435,19290,−23435,−13870,−158,−11435,83870,0,27290,139870,0,487,28145,43435,19145,24145,−7290,1145,115,14145,23145,−13435,−2145,1174,−158,3145,53870,2145,7870,187,13145,−14435,18145,487,−158,28145,8145,83870,−28435,−43870,−287,−13870,2435,−3145,130,43435,1145,−587,−43435,−23435,−23870,−5174,23174,23870,0,−19290,−11435,27290,−17870,−73870,14435,−158,−7145,−22435,−17290,9145,−115,26435,1187,−115,11870,139870,19290] map(abs,FXYL)$ smax(%); (%o41) 28145 ((nX*nY)/(nX+nY))^(1/2)*%; (%o42) 28*870145*59 t:float(%), numer; (%o43) 0.7415213325427759 makelist(2*(-1)^k*exp(-k^2*t^2),k,1,10); (%o44) [−1.154068233257314,0.2217358731762402,−0.01418545976794225,3.021717464758644*10−4,−2.143222576321111*10−6,5.061551714992411*10−9,−3.980183215586646*10−12,1.042138479241532*10−15,−9.085540779783623*10−20,2.637418903432282*10−24] 1+sum(2*(-1)^k*exp(-k^2*t^2),k,1,10); (%o45) 0.05378221373245584 %<0.95; (%o46) 0.05378221373245584<0.95 Feladat Feladat Nyissuk ki a View-ban a Statistics ablakot! load(stats)$
PKEUmXñB–HmimetypePKEUmXQdBV55 5format.txtPKEUmX¯‘ëÆ`c`c ’content.xmlPK§j