Question 1: Explain in your own words what data compression is and why it is useful in computing.

Answer: Data compression reduces the size of data to save storage space and improve transmission efficiency. It is useful because it allows faster data transfer and less storage requirement.

Question 2: Describe the difference between lossless and lossy compression. Provide one example of each.

Answer: Lossless compression reduces data size without losing any information, e.g., ZIP files. Lossy compression reduces data size by removing some information, e.g., JPEG images.

Question 3: Identify two common algorithms used for lossless data compression and briefly describe how they work.

Answer: Huffman coding assigns shorter codes to more frequent symbols, reducing overall size. Run-length encoding replaces repeated sequences with a count and a single value.

Question 4: A text file contains the phrase 'HELLO HELLO HELLO'. Explain how run-length encoding could compress this data.

Answer: Run-length encoding could replace the repeated 'HELLO' with a count, such as '3 x HELLO', reducing redundancy and file size.

Question 5: Complete the truth table for a NOT gate. The table should include the input (A) and the output (Q).

Answer: A | Q 0 | 1 1 | 0

Question 6: Draw a logic circuit for an AND gate. Label all inputs and outputs clearly.

Answer: A correct sketch will show a standard AND gate shape with two inputs (A and B) entering from the left, and one output (Q) exiting from the right.

Question 7: Using logic gates, design a circuit that outputs true only when exactly one of two inputs is true. Draw your circuit.

Answer: A correct circuit will use XOR gate or a combination of AND, OR, and NOT gates to produce output true only when one input is true.

Question 8: Explain how data compression can help reduce the load on network bandwidth during data transmission.

Answer: Compressed data takes up less space, meaning less data needs to be transmitted over the network, resulting in faster transfer speeds and less congestion.

Question 9: A digital image uses 24 bits per pixel. If the image is compressed using a lossless method reducing size by 25%, how many bits per pixel does the compressed image effectively use?

Answer: After 25% reduction, each pixel uses 18 bits (since 75% of 24 bits is 18 bits).

Question 10: Sketch a diagram showing how Huffman coding assigns shorter binary codes to more frequent characters in a dataset. Use at least three characters with different frequencies.

Answer: A correct sketch will include a binary tree where the most frequent character has the shortest code, and less frequent characters have longer codes, illustrating variable-length coding.