# Which Of The Following Is True Of How Computers Represent Numbers?

Which Of The Following Is True Of How Computers Represent Numbers?

Computers are an integral part of our daily lives, but have you ever wondered how they represent numbers? Understanding this fundamental aspect of computer science is essential for comprehending the inner workings of these machines. In this article, we will explore the truth behind how computers represent numbers and delve into some interesting facts about this topic.

1. Binary System: Computers use the binary system to represent numbers. Unlike humans, who use the decimal system (base-10), computers operate in base-2. This means that they only understand two digits, 0 and 1, which are called bits. Each bit represents a single binary digit.

2. Bits and Bytes: A bit is the smallest unit of information in a computer. Eight bits make up a byte, which is the basic unit for storing information. Bytes are commonly used to measure file sizes, memory capacities, and data transmission rates.

3. Two’s Complement: Computers use the two’s complement representation to store negative numbers. In this system, the leftmost bit is reserved as the sign bit. If the sign bit is 0, the number is positive, and if it is 1, the number is negative. This method simplifies arithmetic operations, as the computer can perform addition and subtraction using the same logic for both positive and negative numbers.

4. Floating-Point Representation: Computers use floating-point representation to handle decimal numbers. This method breaks down a number into three components: the sign, the exponent, and the mantissa. The exponent determines the scale of the number, while the mantissa represents the significant digits. Floating-point representation allows computers to accurately represent very large or very small numbers.

5. ASCII Encoding: Computers also use a standardized system called ASCII (American Standard Code for Information Interchange) to represent characters. Each character is assigned a unique number, which is stored as a binary value. This encoding system enables computers to process and display text.

Q1. Why do computers use the binary system instead of the decimal system?
A1. Computers use the binary system because it is easier to implement in electronic circuitry, which is the foundation of computer hardware. The binary system aligns well with the behavior of electronic switches, which can be either on (1) or off (0).

Q2. How are numbers larger than one represented in binary?
A2. In binary, numbers larger than one are represented by combining multiple bits. Each bit’s position represents a power of 2, allowing for the representation of larger numbers by adding the corresponding powers.

Q3. Can computers represent irrational numbers?
A3. Computers cannot precisely represent irrational numbers like π or √2. Instead, they use approximations to represent these numbers to a certain level of precision.

Q4. How does a computer store and manipulate fractions?
A4. To store fractions, computers use fixed-point or floating-point representations. Fixed-point representation allocates a specific number of bits for the integer and fractional parts of a number, whereas floating-point representation allows for more flexibility and precision.

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Q5. Can computers handle complex numbers?
A5. Yes, computers can handle complex numbers. Complex numbers are represented using two floating-point numbers, one for the real part and the other for the imaginary part.

Q6. How do computers round numbers?
A6. Computers use various rounding algorithms, such as rounding towards zero, rounding towards infinity, rounding to the nearest even number, or rounding away from zero. The specific algorithm depends on the programming language and the context.

Q7. Are there limits to the range of numbers computers can represent?
A7. Yes, computers have finite storage capacities, which means they have limits on the range of numbers they can represent. The size of the storage determines the maximum and minimum values that can be stored.

Q8. How do computers convert between different number systems?
A8. Computers can convert numbers from one base to another by using algorithms such as the long division method or the repeated division method. These algorithms perform successive divisions and record the remainders to convert a number from one base to another.

Q9. Can computers represent imaginary numbers?
A9. Yes, computers can represent imaginary numbers using floating-point numbers. The real part is stored in one floating-point number, while the imaginary part is stored in another.

Q10. How are characters represented in computers?
A10. Characters are represented using ASCII encoding. Each character is assigned a unique binary code, allowing computers to store, process, and display text.

Q11. Can computers represent non-numeric data?
A11. Yes, computers can represent non-numeric data using various encoding schemes. For example, images can be represented using RGB values, and audio can be represented using waveform data.

Q12. How do computers handle numbers with decimal places?
A12. Computers use floating-point representation to handle numbers with decimal places. The decimal part is represented using the mantissa, while the exponent determines the scale of the number.

Q13. Can computers perform exact arithmetic with decimal numbers?
A13. Due to the limitations of floating-point representation, computers cannot perform exact arithmetic with decimal numbers. Small rounding errors may occur during calculations.

Q14. Are there alternative number systems used in computers?
A14. While binary is the primary number system used in computers, there are alternative number systems such as octal (base-8) and hexadecimal (base-16). These systems are often used in programming to represent binary values more concisely.

Understanding how computers represent numbers is crucial for programmers, engineers, and anyone curious about the inner workings of these machines. The binary system, bits and bytes, two’s complement, floating-point representation, and ASCII encoding are the key concepts to comprehend. With this knowledge, we can appreciate the complexity and precision with which computers handle numbers and data.

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