GCSE CS Data revision

Binary
1. Using binary
  1. Binary is used to represent data and program instructions as 1's and 0's
  2. 1 bit = can have 2 combinations 2 bits = can have 4 combinations
2. Converting Binary to Denary
3. Converting Denary to Binary
4. Binary Addtion
  1. 0+0 = 0 1+0 = 1 1+1 = 10 1+1+1 = 11
  2. Overflow error - occurs when a calculation produces a result that is greater then the computer can deal with e.g. if from an 8 bit addition you require a 9th bit
5. Logical Shifts
Signed integers
1. Two's complement
  1. Converting Two's complement
    1. converting a number - step 1 - flip the 0's with 1's and 1's with 0's Step 2 - add Denary one to the binary digit
  2. Adition Two's complement
    1. This is the same as normal addition, but you must convert the numbers to two's complement first
  3. This format 0 can only be represented one way as 000000 and calculations are always accurate.
2. Arithmetic shifts
  1. this is the same as logical shift, however the MSB will stay the same.
3. This is used to represent negative numbers within binary, with a most significant bit (MSB) is used to show a positive ore negative number. The leftmost bit shows if the number positive (with a 0) or negative (with a 1).
  1. The issues is that you can only Represent 128 combinations as the 8th bit is the MSB
  2. Also using this method 0 can be both positive and negative 10000000 or 00000000
Hexadecimal
1. Used to help humans cope with long strings of binary digits (they are shorther) It is used to represent errors within a computer
Characters
1. Computers represent text, numbers and symbols as binary strings of 1's and 0's
2. ASCII - is a way of represent text as an 8 bit code which can hold 256 characters. Each characters has a binary number e.g. A = 01000001
3. You can find ASCII codes with some pre-built function from Pseudo code. The ord() function returns the number e.g. ord("C") would shown 99. The chr() function returns the letter e.g. chr("99") would shown c
Images
1. Computers represent images as a sting of 1's and 0's
2. An images is made up of small points of colours called pixels, with each one having its own colour, the more pixels the more ddetail will be shown within the image
3. Colour depth = the number of bots used to encode the colour of each pixel, the more bots uses the more colours can be represented e.g. 8 bits or a colour depth of 8 would show 256 colours within the image
4. Resolution = the number of pixels within the image
5. Calculating file size = width x height x colour depth
Sounds
1. Computers represent images as a sting of 1's and 0's via analogue to digital recording
2. Sound sampling - samples of sounds waves are taken at regular fixed intervals.
3. Bit depth - the number of bits used to encode each sound sample. Higher the bit depth the more accurate recording with a bigger sound file e.g. a bit depth of 24-bits would have 16.7 million combinations
4. Sample frequency x bit depth x length of recording (in seconds)
Units
1. This denotes the size of a file (to make it easy to identify through different units)
2. To convert between different units we need to multiply or divide. E.g. 2341200000 bits to GB’s - 2341200000 / 8 /1024/1024/1024 = 0.27GB’s
Data Compression
1. Lossless compression - reduces the file size without deleting any data via grouping some data - good for text files
  1. Run-Length encoding
    1. This is lossless compression algorithm to get reduce a file size through the removal of duplicate data
2. Lossy compression - deleting some data from the file which you cannot get back through taking out very small veriations in sounds which humans era cannot detect. e.g. good for videos and images, JPG and MP3 an examples of this compression
3. Compression is needed for less internet band width for downloading, transfer speed faster, less storage space, so you can stream online
Databases
1. Unstructured data - data that is not orgonised. Structured data - data that is stored in an organised and ordered way so that it can searched. e.g a database
2. A Databases is a persistent and organised store of data
3. Entities - are a thing which is recognised as being capable of an independent existence and which can be uniquely identified.
  1. e.g Students will be entities within a database with Attributes of name, ID, Year, Age
4. Tables are used to represented each entity with attributes as the column (a field) and a Row is a record of data
5. Primary Key - a unique identifier that cannot be duplicated within a table (e.g. Book_ID)
6. Relational databases
  1. A database which has multiple tables and can be linked to reduce data redundancy
  2. A relational database allows data elements in one table to be related to any piece of data in another table so long as a Foreign key is within the table
    1. Foreign key - so tables can be linked, this is a primary key on one table and is on another table as a foreign key
  3. No data inconsistency – as data is not duplicated, there is no risk of the same data item being stored differently in another record.
  4. No data redundancy – in a well-designed relational database there should be no duplicated data (other than the key field).
Encryption
1. Data should be encrypted to ensure that unauthorised people cannot read it. Encryption is a way of scrambling of data intoa form that cannot be understood by unauthorised people
2. Encryption protocols - HTTPs with the SSL in the transport layer and TLS protocol added to the message
3. Asymmetric encryption
  1. This method encrypts and decrypts data using 2 different keys. Each user a public key (known to everyone) and a private key (only know by themselves) . A message can only be decrypted by the corresponding private key
4. Symmetric encryption
  1. This method uses the same key to encrypt and decrypt data. This is the method used by HTTPs
5. The Caesar Cipher
  1. his is a simple encryption method and would not be used today because it is so easy to crack. The letters of the alphabets are shifted a set number of places. A positive shift the the right and a negative shift to the left

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GCSE CS Data revision

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	Created by Simon Howe almost 7 years ago