* Đồ thị hàm số, hàm số, đồ thị. Mấy cái này khác nhau như thế nào vậy ạ? Lấy ví dụ giúp mình nhá!
*Tìm tọa độ giao điểm của 2 đồ thị
+ Tọa độ giao điểm của 2 đồ thị nghĩa là như nào ạ?
+ Nếu làm theo cách vẽ đồ thị thì đối với trường hợp nào. Và cách giải theo vẽ đồ thị hàm số như nào ạ?
+ Với nhiều hàm số trở lên thì làm như nào ạ?
+ Hoành độ giao điểm của 2 đồ thị là nghiệm của phương trình. Tại sao là hoành độ giao điểm mà không phải tung độ giao điểm ạ?
+ Ví dụ y= -2x+3 (d1). Mình gọi (d1) là đường thẳng. Đường thẳng này khác với hàm số như nào ạ. Ví dụ thay x = 2 vào (d1) thì không đung mà phải nói thay x = 2 vào y = -2x+3 thì mới đúng ạ? Mà mình đặt hàm số đó là đường thẳng (d1) vậy tại sao khác nhau như nào ạ?
Lời giải:
Nói đơn giản thế này. Khi đề cho: Cho đồ thị hàm số $y=x+2$
- Hàm số: chính là $y=x+2$, biểu diễn mối quan hệ giữa biến $x$ và biến $y$. Hàm số hiểu đơn giản giống như phép biểu diễn mối quan hệ giữa hai biến.
- Đồ thị hàm số (hay đồ thị): Khi có hàm số rồi, người ta muốn biểu diễn nó trên mặt phẳng tọa độ ra được 1 hình thù nào đó thì đó là đồ thị hàm số. Ví dụ, đths $y=x+2$ có dạng như thế này:
![](data:image/png;base64,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)
- Tọa độ giao điểm của hai đồ thị: Khi ta vẽ được đồ thị trên mặt phẳng tọa độ, 2 đồ thị đó giao nhau ở vị trí nào thì đó chính là tọa độ giao điểm. Ví dụ, trên mp tọa độ ta có 2 đồ thị $y=-2x+3$ và $y=x+6$ chả hạn. Điểm $A$, có tọa độ $(-1,5)$ chính là giao điểm. Như vậy, $(-1,5)$ là tọa độ giao điểm.
- Nhìn hình vẽ của đồ thị chỉ giúp ta có cái nhìn trực quan hơn. Khi muốn tìm giao điểm của 2 đồ thị hàm số, người ta thường dùng hàm số để tìm cho nhanh, vì hàm số biểu diễn mối quan hệ giữa hai biến một cách "số hóa" hơn.
- Với nhiều hàm số trở lên thì ta cứ xét từng cặp 1 thôi.