Data and Information
FoundationData are raw facts and figures with no meaning on their own; after collection, validation, organisation, analysis and presentation, they become meaningful and useful information. Mastering the input-process-output cycle and validation is the first step of information processing.
- Data are raw unprocessed facts; information is the meaningful, useful result of processing
- Computers process data through the input-process-output cycle
- Common collection methods: questionnaires, interviews, observation, existing records
文體小知識：科技知識說明文——講解數據與資訊的分別、輸入－處理－輸出的處理流程，以及把原始數據變成有用資訊的方法。
§Text Passage
1Data are raw facts, figures, text or symbols that have not been processed and lack context, so on their own they may carry no meaning. For example, the three numbers 38, 45 and 40 mean nothing until we know they are the heights (in centimetres) of three Secondary 4 students. Information is the result of processing data into a form that has meaning and purpose, helping people understand situations, answer questions and make decisions.
2Computers process data through the input-process-output cycle: data is entered through keyboards, questionnaires or sensors; the computer classifies, sorts, calculates and summarises it; and the output is information such as tables, charts or reports. For example, a school enters the whole class's test scores into a spreadsheet, calculates the mean and the score distribution, and issues a chart for teachers and students — a typical information processing workflow.
3Before processing, the quality of the data decides success or failure. Common collection methods include questionnaires, interviews, observation and consulting existing records, each with strengths and weaknesses. Input should pass validation checks — for instance, rejecting a negative age or irrelevant text in a gender field — so that unreasonable data is kept out; otherwise garbage in, garbage out: even the most precise processing cannot produce trustworthy information.
4Useful information should be accurate, relevant, complete and timely. When people understand and reflect on information using experience and thinking, it becomes knowledge that explains phenomena and guides action. For example, a report showing the class average fell by five marks is information; the teacher judging that a unit was taught too fast and adjusting the pace is the use of knowledge. Data, information and knowledge build on one another and form the basis of decisions.
1Summary 重點摘要
Data are raw facts and figures with no meaning on their own; after collection, validation, organisation, analysis and presentation, they become meaningful and useful information. Mastering the input-process-output cycle and validation is the first step of information processing.
2Vocabulary cards Vocabulary
Raw facts, figures, text or symbols that have not been processed and have no clear meaning on their own.
Data processed into a meaningful and useful form that helps people understand situations and make decisions.
The basic model of data processing: data is input, processed by the computer, and output as information.
Gathering raw data through questionnaires, interviews, observation or existing records.
Checks applied to input data so that unreasonable or impossible values are rejected.
If the input data is wrong, the output information will be wrong too, no matter how precise the processing.
Application software that organises data in rows and columns and performs calculations and charts.
A chart that uses the lengths of bars to compare quantities across categories.
Information absorbed through human understanding, experience and thinking, and applied to explain and decide.
3Step by step Steps
- Step 1: What data isData are raw facts, figures, text or symbols that have not been processed; without context they are hard to interpret. For example, the three numbers 38, 45 and 40 mean nothing until we know they are the heights of three students in centimetres. Remember the two features of data — unprocessed and meaningless on its own — which distinguish it from information and are often examined.
- Step 2: What information isInformation is data that has been processed into something meaningful and useful, helping people understand situations, answer questions and decide. For example, turning forty scores into a mean of 62.5 and a distribution chart lets a teacher see overall performance and who needs support at a glance — those organised results are information. Anchor answers on organised, meaningful and useful.
- Step 3: The input-process-output cycleComputers process data through the input-process-output cycle: input devices enter the data, the computer classifies, sorts, calculates and summarises as needed, and the output appears as tables, charts or reports. For example, a supermarket scans every sale at the till, the system tallies daily sales of each product and prints a report, and the manager orders stock accordingly — a complete application of the cycle.
- Step 4: Data collection methodsCommon methods are questionnaires, interviews, observation and consulting existing records, each with pros and cons. For example, to survey lunch preferences across a whole school, a questionnaire reaches many students quickly; interviews probe reasons in depth but take time; observing actual canteen choices verifies whether answers are truthful. Choose by headcount, depth needed and time cost, and justify the choice in the report.
- Step 5: ValidationData should pass validation before and after entry to ensure values are reasonable: range checks (age cannot be negative), type checks (a gender field cannot hold numbers) and format checks (no thirteenth month). For example, a survey system set to accept scores only from 0 to 100 instantly prompts re-entry when 150 is typed, keeping bad data out of the database. This is the first line of defence for reliable information.
- Step 6: Garbage in, garbage outIf the input data is wrong, the output information will be wrong no matter how precise the processing — garbage in, garbage out. For example, entering a student's score of 78 as 8 distorts the mean and every chart, and the teacher may decide on false grounds. So validate before processing and sample-check against the raw data afterwards; only double checking produces trustworthy information.
- Step 7: From information to knowledgeUseful information is accurate, relevant, complete and timely; understood and reflected upon, it becomes knowledge. For example, a report showing the class average fell five marks from last term is information; the teacher drawing on experience to conclude that a unit was taught too fast, then slowing down and adding tutorials, is knowledge at work. Data, information and knowledge build layer by layer into decisions.
4Diagrams Diagrams
5Worked example Example
A class of S4 students surveyed 40 students on their daily mobile phone use, and now must turn the raw questionnaire data into a report. Describe the processing workflow and compute the relevant statistics.
- Validate and clean: apply validation first and remove invalid questionnaires, such as those with negative times or irrelevant text; 38 valid responses remain.
- Organise the data: sort the 38 values and tally by group — 6 students under 1 hour, 12 between 1 and 2 hours, 14 between 2 and 3 hours, and 6 over 3 hours.
- Compute statistics: using group midpoints, total use ≈ 6×0.5 + 12×1.5 + 14×2.5 + 6×3.5 = 77 hours, so the mean is 77 ÷ 38 ≈ 2.0 hours per student.
- Present the information: draw a bar chart of the four time bands; the 2–3 hour group is the largest and the most common pattern.
- Conclude and recommend: 14 + 6 = 20 students exceed two hours, 20 ÷ 38 × 100% ≈ 52.6%; recommend a talk on healthy phone use.
- Answer: The workflow has four steps. First, validation: invalid questionnaires are removed, leaving 38 valid responses. Second, organisation and analysis: the values are sorted and tallied into four time bands; using midpoints, total use is about 77 hours and the mean is 77 ÷ 38 ≈ 2.0 hours per student. Third, presentation: a bar chart shows the distribution, with the 2–3 hour band the largest. Fourth, conclusion: 20 ÷ 38 × 100% ≈ 52.6% exceed two hours a day, supporting a recommendation for a healthy-use talk. The process illustrates the input-process-output cycle, with validation guarding against garbage in, garbage out.
6Common mistakes Mistakes
7Quick check Quick check
Q1What is the difference between data and information?
Q2State the basic model of how computers process data.
Q3What is garbage in, garbage out?
Q4Of 40 students surveyed, 38 valid responses were collected and 20 use their phone over two hours a day. Find the percentage.
Q5Give two common methods of data collection.
8Recap Recap
- Data are raw unprocessed facts; information is the meaningful, useful result of processing
- Computers process data through the input-process-output cycle
- Common collection methods: questionnaires, interviews, observation, existing records
- Validation rejects unreasonable data, preventing garbage in, garbage out
- Good information is accurate, relevant, complete and timely; reflected upon, it becomes knowledge