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Learn about how to convert between the denary (decimal), binary and hexadecimal number systems. Based on the J277 OCR GCSE Computer Science specification (first taught from 2020 onwards). Exam Board: OCR 2.4a: Number Systems Specification: J277 Watch on YouTube : Binary and Denary Hexadecimal Number System Ranges Binary to Denary Denary to Binary Binary to Hexadecimal Hexadecimal to Binary Denary to Hexadecimal Hexadecimal to Denary What is binary? By now you should know that computer systems process data and communicate entirely in binary . Topic 2.3 explained different binary storage units such as bits (a single 0 or 1), nibbles (4 bits) and bytes (8 bits). Binary is a base 2 number system. This means that it only has 2 possible values - 0 or 1 . What is denary? Denary (also known as decimal ) is the number system that you've been using since primary school. Denary is a base 10 number system. This means that it has 10 possible values - 0, 1, 2, 3, 4, 5, 6, 7, 8, and 9 . Binary & Denary Convert from binary to denary: Convert from denary to binary: Hexadecimal What is hexadecimal? Hexadecimal is a base 16 number system. This means that it has 16 possible values - 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, A, B, C, D, E and F . Hexadecimal is used as a shorthand for binary because it uses fewer characters to write the same value . This makes hexadecimal less prone to errors when reading or writing it , compared to binary. For example, 100111101011 in binary is 9EB in hexadecimal. Hexadecimal only uses single-character values. Double-digit numbers are converted into letters - use the table on the right to help you understand. Binary to hexadecimal: Hexadecimal to binary: Converting from denary to hexadecimal / hexadecimal to denary To convert from denary to hexadecimal or from hexadecimal to denary , it is easiest to convert to binary first . However, it is possible to convert directly from denary to hexadecimal or directly from hexadecimal to denary . The videos below explain both methods . Denary to hexadecimal: Hexadecimal to denary: Watch on YouTube Watch on YouTube Watch on YouTube Watch on YouTube Watch on YouTube Watch on YouTube Q uesto's Q uestions 2.4a - Number Systems: 1. Explain why hexadecimal numbers are used as an alternative to binary . Use an example . [ 3 ] 2. Convert the following values from binary to denary : a. 00101010 b. 11011011 c. 01011101 d. 11101110 e. 01011111 [1 each ] 3. Convert the following values from denary to binary : a. 35 b. 79 c. 101 d. 203 e. 250 [1 each ] 4. Convert the following values from binary to hexadecimal : a. 11110101 b. 01100111 c. 10111010 d. 10010000 e. 11101001 [1 each ] 5. Convert the following values from hexadecimal to binary : a. C2 b. 8A c. DE d. 54 e. F7 [1 each ] 6. Convert the following values from denary to hexadecimal : a. 134 b. 201 c. 57 d. 224 e. 101 [1 each ] 7. Convert the following values from hexadecimal to denary : a. 32 b. A5 c. 88 d. C0 e. BE [1 each ] Click the banners below to try self-marking quizzes (Google Forms) on these topics. Binary to Denary: Denary to Binary: Binary to Hexadecimal: Hexadecimal to Binary: 2.3 - Data Units Theory Topics 2.4b - Binary Addition & Shifts

Learn about each of the 8 stages of data analysis including exactly what should occur at every stage. Based on the 2016 OCR Cambridge Technicals Level 3 IT specification for Unit 2 (Global Information). 3.4 - Stages of Data Analysis Exam Board: OCR Specification: 2016 - Unit 2 Data analysis is the process of identifying and collecting data to be viewed and modelled, in the aim of discovering patterns or trends that can be used for conclusions and decision-making. 1. Identify the need Before anything else can take place, objectives are set for what the data analysis will hope to achieve. Aims must be clear and well defined . For example, an organisation should define what information will be needed and what exactly they want to find out by the end of the process (the purpose of the data analysis). Not clearly defining the required information or purpose could lead to worthless results and a waste of the entire data analysis process. 2. Define the scope In this stage the restrictions of the project are defined. Scope includes factors such as budget , content , detail , timescales (deadlines) and any further constraints . 3. Identify potential sources Project planners must identify a wide range of sources for the potential information, ensuring that it is unbiased and covers the objectives . The specific data will depend on the project but it could include sales figures or customer surveys for example. 4. Source and select information Information is gathered from the identified sources in stage three. Any unsuitable data is excluded so that results are not unreliable as poor quality information can lead to numerous negative consequences . Planners will have to determine the accuracy and reliability of any identified sources and select the best . 5. Select the most appropriate tools There are many different data analysis tools that can be used as part of this sequence; in this stage the most appropriate tool for the project is selected. Examples include methods of presentation such as charts and graphs for a visual representation of data . Regression analysis can also be used - regression is the determining of relationships e.g. if the amount spent on advertising bottled water increases, will consumption increase too or are other factors involved? If there is a link, a business can continue to spend more on advertising if consumption and profit also rises. Trend analysis is another option - this shows patterns over time , for example, bottled water consumption each year over the past decade. 6. Process and analyse data Data has now been collected and can be inputted into software such as spreadsheets or databases to further analyse. Putting collected data into a spreadsheet for example allows for analysis to begin as graphs can be created from the data and any patterns or trends discovered. 7. Record and store information The data has been collected and analysed and now any findings are written into a report . Any patterns, trends or findings can be described with statistical evidence generated from the analysis. 8. Share results A report is worthless if not shared with the stakeholders . Sharing can take different forms such as a typed document posted out to stakeholders, an email with major findings summarised or as a post on a website . Q uesto's Q uestions 3.4 - Stages of Data Analysis: 1. List the 8 stages of data analysis in order. [8 ] 2. A supermarket chain called 'Fresh Food UK' wants to complete data analysis to see which stores across the country have been most profitable in the last year . Explain how Fresh Food UK would use each of the 8 stages of data analysis . [16 ] 3.2 & 3.3 - Information Categories Topic List 3.5 - Data Analysis Tools

Learn about defensive design considerations including validation checks, verification, anticipating misuse, maintainable code, authentication and input sanitisation. Based on the J277 OCR GCSE Computer Science specification (first taught from 2020 onwards). 3.1: Defensive Design Exam Board: OCR Specification: J277 Watch on YouTube : Defensive Design Validation Checks Maintainability Defensive Design Considerations There are several things to consider when creating a program that is secure and robust , including: Anticipating Misuse Planning ahead to take steps against potential misuse (e.g the app X prevents the same tweet sent twice in a row as it might be spam ). Input Sanitisation Checking and cleaning up data that has been input , (e.g. removing special characters to prevent a SQL injection ). Validation Checking whether input data follows specific criteria and should be accepted (e.g. a length check on a password). Verification Checking whether data that has been entered is correct (e.g. double entry ). Authentication Ensuring only authorised users can gain access to a system (e.g. usernames and strong passwords ) . Maintainable code Allowing other programmers to easily read and quickly understand code that has been written (e.g. using comments , indentation and appropriate variable names ). Input Validation Validation is a process to check that data is reasonable or sensible before it is accepted . Range Check Checks data is within a certain range . Age: 34 203 Type Check Checks data is a certain data type . Height (in cm): 182 Two metres Format Check Checks data is entered in a certain way . Date of Birth (DD/MM/YYYY) 25/03/2011 25th March 11 Presence Check Checks that data has actually been entered and not left blank . Password: fluffythecat123 Lookup Table A table of acceptable entries , also known as a list . Length Check Checks the length of the input is within a certain amount. Telephone Number 08323877319 07383 Maintainability Programs should be written in a way that makes maintaining and understanding them as straightforward as possible. Examples of making a program maintainable include: Using subprograms to reuse code and make them easier to test . This is called modularisation . Appropriate variable names , using a naming convention , ensure the purpose of a variable is immediately understood. Using indentation to improve readability and clearly show each ‘block’ of code. Comments enable a programmer to understand the purpose of each line of code. Crucial when working in a team . Using constants is another method of improving maintainability. This keeps the program code consistent , which makes it easier to read and debug a program. Q uesto's Q uestions 3.1 - Defensive Design: 1. Describe the different considerations a programmer should make for a defensive design . [ 6 ] 2. Describe the each validation check and give a suitable example . [ 12 ] 3. Explain the different ways a program can be maintained . [ 5 ] 2.3 Additional Programming Theory Topics 3.2 - Testing

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