Floating-point number is a widely used data type in computer programming. Floating-point numbers consist of mantissa and exponent. The mantissa represents the actual value, while the exponent represents the displacement of the mantissa. This data type can be used to store decimals, not just integers.

The precision of floating-point numbers is determined by the size of the exponent. The size of the exponent will affect the range of the maximum and minimum values that floating-point numbers can represent. When using floating-point numbers to calculate, we need to pay attention to the problem of accuracy. Because floating-point numbers are not completely accurate digital representations, there may be precision errors when performing operations such as addition, subtraction, multiplication and division.

Floating point numbers can be represented by different data types, such as single-precision floating point numbers and double-precision floating point numbers. Single-precision floating-point numbers are represented by 4 bytes and double-precision floating-point numbers by 8 bytes. Because the precision of double-precision floating-point number is higher, it is more suitable to choose double-precision floating-point number for data representation in some application fields that need high-precision calculation.