Γραφικός υπολογιστής τσέπης CASIO FX-9860GIII-ET με 64 KB RAM, γραφική οθόνη

Casio FX-9860GIII is a scientific graphing calculator suited for advanced mathematics, engineering and technical education. It features a high-resolution graph display and built-in functions for algebra, calculus, statistics and matrix operations, and includes 64KB of RAM for storing programs and data.

Advantages

The FX-9860GIII delivers a clear, high-resolution screen for detailed graphing and data visualization and provides a broad set of mathematical and statistical functions. Its intuitive menu layout and programmable capabilities allow users to save routines for repeated calculations. The calculator supports common graph types, equation solving, matrix operations and complex-number calculations, making it practical for classroom and professional use.

Suitable for

• Students in advanced mathematics and engineering courses
• Teachers and instructors preparing classroom demonstrations
• Professionals needing on-device graphing and numeric computation

Key specifications

• Graphical display with high resolution suitable for plotting functions and visual analysis
• 64KB RAM for programs and data storage
• Built-in functions for algebra, calculus, statistics, matrix operations and complex numbers
• Programmable interface and menu-driven operation for repeatable tasks

How to use

Power on the calculator and choose the mode matching your task, such as graph, calculation or statistics. Use the menu keys to select functions, enter expressions via the keypad and press the execute key to compute results or render graphs. Store frequently used routines in the programmable memory and navigate outputs with the cursor keys. Consult the user manual for step-by-step procedures for advanced features like matrix manipulation and equation solvers.

Recommendations

Use the FX-9860GIII for coursework and exams where graphing calculators are allowed; confirm permitted models before examinations. Keep saved programs backed up and refer to the manual for model-specific limitations when working with large matrices or complex programs.