MATLAB Basic Data Types: Numeric, Integer, Symbolic sym, String, Class Variables

# 2.1 Numerical Data Types

Numerical data types are used to represent real numbers. In MATLAB, there are two types of numerical data types: single-precision floating-point and double-precision floating-point.

### 2.1.1 Single-precision Floating-point

Single-precision floating-point numbers are stored in 32 bits and can represent real numbers in the range of -3.4028235e+38 to 3.4028235e+38. They are typically used for storing data that does not require high precision, such as intermediate results in scientific calculations.

% Creating a single-precision floating-point number
x = 1.2345;

% Viewing the data type
class(x)
% Output: 'single'

# 2. Numerical and Integer Data Types

### 2.1 Numerical Data Types

Numerical data types are used to represent real numbers, including single-precision and double-precision floating-point numbers.

#### 2.1.1 Single-precision Floating-point

Single-precision floating-point numbers use 32 bits of storage, with 1 bit for the sign, 8 bits for the exponent, and 23 bits for the significand. Their value range is [-3.4028235e38, 3.4028235e38], with a precision of about 7 decimal places.

% Creating a single-precision floating-point number
a = single(3.1415926);

% Viewing the data type and value
disp(['Data type: ', class(a)]);
disp(['Value: ', num2str(a)]);

**Logical Analysis:**

* The `single` function converts double-precision floating-point numbers to single-precision floating-point numbers.
* The `class` function returns the data type of the variable.
* The `num2str` function converts numbers to strings.

#### 2.1.2 Double-precision Floating-point

Double-precision floating-point numbers use 64 bits of storage, with 1 bit for the sign, 11 bits for the exponent, and 52 bits for the significand. Their value range is [-1.***e308, 1.***e308], with a precision of about 15 decimal places.

% Creating a double-precision floating-point number
b = double(3.1415926);

% Viewing the data type and value
disp(['Data type: ', class(b)]);
disp(['Value: ', num2str(b)]);

**Logical Analysis:**

* The `double` function converts single-precision floating-point numbers to double-precision floating-point numbers.
* The `class` function returns the data type of the variable.
* The `num2str` function converts numbers to strings.

### 2.2 Integer Data Types

Integer data types are used to represent integers, including signed and unsigned integers.

#### 2.2.1 Signed Integers

Signed integers use 32 bits of storage, with 1 bit for the sign and the remaining 31 bits for representing integers. Their value range is [-2^31, 2^31-1].

% Creating a signed integer
c = int32(-12345);

% Viewing the data type and value
disp(['Data type: ', class(c)]);
disp(['Value: ', num2str(c)]);

**Logical Analysis:**

* The `int32` function creates a 32-bit signed integer.
* The `class` function returns the data type of the variable.
* The `num2str` function converts numbers to strings.

#### 2.2.2 Unsigned Integers

Unsigned integers use 32 bits of storage, with all bits dedicated to representing integers. Their value range is [0, 2^32-1].

% Creating an unsigned integer
d = uint32(12345);

% Viewing the data type and value
disp(['Data type: ', class(d)]);
disp(['Value: ', num2str(d)]);

**Logical Analysis:**

* The `uint32` function creates a 32-bit unsigned integer.
* The `class` function returns the data type of the variable.
* The `num2str` function converts numbers to strings.