Year 9 Computing: Autumn Assessment

Personal data is any information that can be used to identify a living person, such as a name together with an address, a date of birth, a photograph or an email address.

You have the right to have data corrected if it is wrong, and the right to have your data deleted when there is no longer a good reason for the organisation to keep it. You can also object to your data being used for particular purposes, such as marketing.

Writing the place values 128, 64, 32, 16, 8, 4, 2, 1 above the columns: 128 fits into 173 leaving 45, 64 does not fit, 32 fits leaving 13, 16 does not fit, 8 fits leaving 5, 4 fits leaving 1, 2 does not fit and 1 fits leaving 0. Reading the columns gives 10101101.

Split the eight bits into two groups of four, giving 1101 and 0110. The group 1101 is 8 + 4 + 1, which is 13, and 13 is written as D in hexadecimal. The group 0110 is 4 + 2, which is 6. So the answer is D6.

Adding from the right: 0 plus 1 is 1, 0 plus 0 is 0, 1 plus 1 is 0 carry 1, 1 plus 0 plus the carry is 0 carry 1, 0 plus 1 plus the carry is 0 carry 1, 1 plus 1 plus the carry is 1 carry 1, 1 plus 0 plus the carry is 0 carry 1, and 0 plus 0 plus the carry is 1. The answer is 10100001, which is 161 in denary, and 108 plus 53 does equal 161. It fits into eight bits, so there is no overflow.

Overflow happens when the answer to an addition is too large to fit into the number of bits available. A carry is produced out of the leftmost column, but with only eight bits there is no ninth bit to hold it, so the carry is lost and the value that gets stored is not the correct answer.

The number of pixels is 800 multiplied by 600, which is 480000. Each pixel needs 8 bits, so the image data is 480000 multiplied by 8, which is 3840000 bits. Dividing by 8 gives 480000 bytes, and dividing by 1000 gives 480 kilobytes.

Colour depth is the number of bits stored for each individual pixel, so it decides how many different colours a pixel can be. Increasing the colour depth adds bits to every single pixel in the image, not just to a few of them, so an image with a million pixels gains a million extra bits for each extra bit of colour depth. The total number of bits is width times height times colour depth, so raising the colour depth raises the file size in direct proportion.

A character set such as ASCII gives every character a unique number, and K is 75. The computer converts that number into binary, 01001011, and stores those eight bits. The shape of the letter is never stored: only the code is. When the character needs to be shown on screen, software looks the code up in the same character set and draws the matching symbol, which is why both machines have to agree on the character set for text to appear correctly.

Sixteen is two to the power of four, so one hexadecimal digit stands for exactly four bits and a whole byte becomes just two hexadecimal digits. A memory address written as eight ones and zeros is easy to lose your place in, and a single misread digit gives a completely different address. Written in hexadecimal the same value takes a quarter of the characters, so it is far quicker to read aloud, write down and compare, and far harder to get wrong.

The formula is sample rate times bit depth times seconds times channels. That gives 44100 times 16 times 30 times 1, which is 21168000 bits. Dividing by 8 gives 2646000 bytes, dividing by 1000 gives 2646 kilobytes, and dividing by 1000 again gives approximately 2.6 megabytes.

Increasing the sample rate means the height of the wave is measured more often, so the steps of the digital version are narrower and the recording follows the shape of the original analogue wave far more closely, which improves the sound quality. The cost is size. Every extra sample is another set of bits to store, so the file grows in direct proportion to the sample rate, and a larger file takes longer to send over a network and needs more processing to play back.

There is a real argument for high quality. Keeping more detail matters when a file is going to be edited, printed large or used professionally, because quality lost at the point of capture can never be recovered afterwards. Against that, quality costs size, and the cost is not small: doubling the sample rate or the colour depth roughly doubles the file. Large files fill storage quickly, which either means paying for more or deleting things, and they take much longer to upload, download or stream, which is a serious problem on a slow or metered connection. There is also the question of whether anybody notices. On a phone screen or through cheap earphones, most people genuinely cannot tell a very high quality file from a moderate one, so the extra bits buy nothing. The sensible conclusion is to match the quality to the purpose: capture and archive at high quality when the file will be edited or printed, and store or share a smaller version for everyday use.