Tabellenkalkulation (TK)

Mit GeoGebra können große Datenmengen in Tabellen verwaltet und verarbeitet werden. Dabei ist vor allem die [b]automatische Ausfüllfunktion[/b] von Bedeutung. Sie ermöglicht es, ein bereits vorhandenes Muster systematisch fortzuführen, indem ein markierter Bereich (blauer Kasten) bei gedrückter linker Maustaste auf weitere Zellen (grauer Kasten) übertragen wird.[br][br][img]data:image/png;base64,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[/img]
[b][size=150]Arbeitsauftrag[/size][/b][br]Erstellen Sie im unten stehenden Applet mithilfe der automatischen Ausfüllfunktion eine Spalte mit den natürlichen Zahlen von eins bis zehn. Gehen Sie dabei wie folgt vor: [br][br][list=1][*]Tragen Sie in [i]A1[/i] eine [i]1[/i] ein,[/*][*]Tragen Sie in [i]A2[/i] eine [i]2[/i] ein,[/*][*]Markieren Sie den Bereich [i]A1 : A2,[/i][/*][*]Erweitern Sie den Bereich [i]A1 : A2[/i] auf den Bereich [i]A1 : A10[/i].[/*][/list]
[b][size=150]Arbeitsauftrag[/size][/b][br]Geben Sie im unten stehenden Applet die Funktion [math]f\left(x\right)=0.25x^3-1.25x^2+0.5x+3[/math] in die Eingabezeile der [i]Algebra-Ansicht[/i] ein. Geben Sie [math]=f\left(A1\right)[/math] in die erste Zeile der zweiten Spalte ein und vervollständigen Sie die restlichen neun Zellen mit der automatischen Ausfüllfunktion.

Information: Tabellenkalkulation (TK)