Understanding Data and Information: From Raw Facts to Useful Knowledge Data Processing SS 1 First Term Lesson Notes Week 10

Subject:
Computer Studies / Information Communication Technology (ICT)

Class:
SS 1

Term:
First Term

Week:
Week 10

Reference Materials:

• Online Materials
• Scheme of Work
• Textbooks

Instructional Materials:

• Computer studies resources
• Online resources

Previous Knowledge:
The students have learned about the application of ICT in everyday life in the previous lesson.

Behavioral Objectives:
By the end of this lesson, students should be able to:

1. Define data.
2. Explain the two main types of data.
3. Identify five sources of data.

Content:

Week Ten Topic:
Data and Information

Definition of Data

Data refers to raw, unorganized, or unprocessed facts that need to be processed. Data in its initial form can be simple, random, and seem meaningless until organized and interpreted.

Example of Data:

• Numbers
• Names of objects, places, or animals
• Measurements (height, weight, temperature)
• Observations and descriptions

Data Visualization

Data visualization is the process of displaying data visually, using charts, graphs, or maps. It allows users to recognize patterns, trends, and insights within data, which helps in better decision-making.

Types of Data

Data can be broadly categorized into two types:

1. Qualitative Data:
   • Descriptive information.
   • Example: Colors, textures, names.
2. Quantitative Data:
   • Numeric information.
   • Example: Height, weight, age.

Additional Types of Data

1. Nominal Data:
   • Used to label or name items for identification.
   • Example: Gender, nationality, zip code.
2. Ordinal Data:
   • Data with a specific order.
   • Example: Rankings (1st, 2nd, 3rd), satisfaction levels (Very Satisfied, Satisfied, Not Satisfied).
3. Interval Data:
   • Numeric data with equal intervals between values, but no true zero.
   • Example: Temperature, dates.
4. Ratio Data:
   • Similar to interval data but includes a true zero point.
   • Example: Height, weight, time.

Subdivision of Quantitative Data

• Continuous Data:
  • Data that can take any value within a range, also known as measured data.
  • Example: Age range 0-99, temperature 10-30 degrees.
• Discrete Data:
  • Data that takes only whole numbers and is countable.
  • Example: Number of students in a class, number of cars in a parking lot.

Forms of Data

1. Numeric (e.g., 0-9)
2. Letters (e.g., A-Z, a-z)
3. Symbols (e.g., +, -, %, *, <, >)

Sources of Data

Data can come from various sources depending on its importance. Common sources include:

• Television
• Internet
• Articles
• Government documents
• Newspapers
• Textbooks
• Biographies

Information

Definition of Information
Information is data that has been processed, organized, and given meaning. It is useful and meaningful to users.

Examples of Information

• Student ID cards
• Weather reports
• Report cards
• International passports
• Utility bills (e.g., electricity, water)

Sources of Information

1. Internet
2. Databases
3. Magazines and Newspapers
4. Census boards
5. Documents and Observations

Characteristics of Good Information

1. Relevance: Must be appropriate for its intended purpose.
2. Reliability: Should come from a trusted source.
3. Accuracy: Free from errors, based on processed data.
4. Availability: Accessible when needed.
5. Suitability: Presented in an understandable form for users.

Data Handling

Data handling is the process of managing research data to ensure it is stored, archived, or disposed of securely during and after a research project.

Ways of Handling Data

1. Electronic Methods:
   • Ensures data integrity, using tools like PDAs, CDs, memory cards.
2. Non-Electronic Methods:
   • Includes paper files, journals, and notebooks, requiring manual effort for data processing.

Evaluation Questions

1. Define data.
2. Describe two main types of data.
3. List any five sources of data.

General Evaluation

1. Name five sources of information.
2. Differentiate between data and information.
3. Mention three forms of data.
4. Identify the two types of data.
5. Explain the difference between continuous and discrete data.

Weekend Assignment

1. _____ are raw facts that have not been processed.
   • A. Information
   • B. Data
   • C. Record
   • D. None
   • Answer: B
2. A characteristic of good information that relates to its correctness is _____.
   • A. Reliability
   • B. Availability
   • C. Accuracy
   • D. None
   • Answer: C
3. _____ refers to data that has been processed.
   • A. Data
   • B. Information
   • C. Database
   • D. None
   • Answer: B
4. There are _____ types of data.
   • A. 2
   • B. 3
   • C. 4
   • D. 8
   • Answer: C
5. The process of searching the internet for research information is called _____.
   • A. Primary source
   • B. Online research
   • C. Secondary source
   • D. None
   • Answer: B

Theory

1. List and explain two ways of handling data.
2. Describe four characteristics of good information.

Presentation

1. Step 1: Teacher reviews previous topics.
2. Step 2: Teacher introduces the new topic.
3. Step 3: Students provide their own examples, and the teacher provides guidance and corrections as necessary.

Evaluation Questions

1. Data is __________ information.
   a) processed
   b) unprocessed
   c) organized
   d) meaningful
   • Answer: b
2. Information is data that has been __________.
   a) collected
   b) ignored
   c) processed
   d) repeated
   • Answer: c
3. An example of qualitative data is __________.
   a) age
   b) color
   c) weight
   d) length
   • Answer: b
4. __________ data is numeric information.
   a) Qualitative
   b) Ordinal
   c) Nominal
   d) Quantitative
   • Answer: d
5. __________ data can take any value within a range.
   a) Discrete
   b) Qualitative
   c) Continuous
   d) Nominal
   • Answer: c
6. __________ data is whole and countable, like the number of students in a class.
   a) Continuous
   b) Discrete
   c) Nominal
   d) Qualitative
   • Answer: b
7. An example of nominal data is __________.
   a) temperature
   b) weight
   c) zip code
   d) height
   • Answer: c
8. Data visualization helps display data using __________.
   a) text only
   b) charts and graphs
   c) speeches
   d) music
   • Answer: b
9. __________ is not a form of data.
   a) Symbols
   b) Numeric
   c) Words
   d) Paintings
   • Answer: d
10. Data that has equal intervals but no true zero is __________.
    a) Nominal
    b) Interval
    c) Ratio
    d) Ordinal
    • Answer: b
11. An ID card is an example of __________.
    a) data
    b) raw facts
    c) information
    d) incomplete data
    • Answer: c
12. Which is a characteristic of good information?
    a) Inaccuracy
    b) Unreliable
    c) Suitability
    d) Complexity
    • Answer: c
13. The process of storing data safely is called __________.
    a) data processing
    b) data handling
    c) data collecting
    d) data deleting
    • Answer: b
14. A weather report is an example of __________.
    a) raw data
    b) qualitative data
    c) information
    d) unreliable data
    • Answer: c
15. __________ is an example of an electronic method of data handling.
    a) Paper files
    b) CD/DVD
    c) Notebooks
    d) Journals
    • Answer: b

Class Activity Discussion

1. What is data?
   • Data is raw, unprocessed information.
2. What is information?
   • Information is processed data that is meaningful and useful.
3. Give an example of qualitative data.
   • An example of qualitative data is color.
4. What are two types of data?
   • The two types are qualitative and quantitative data.
5. How does interval data differ from ratio data?
   • Interval data has no true zero, whereas ratio data has a true zero.
6. What is continuous data?
   • Continuous data can take any value within a range.
7. Give an example of discrete data.
   • The number of people in a room is an example of discrete data.
8. What is data visualization?
   • Data visualization is representing data using visuals like charts and graphs.
9. What are the four types of data?
   • Nominal, ordinal, interval, and ratio.
10. What is nominal data?
    • Nominal data is used for naming or labeling, like gender or nationality.
11. What is ordinal data?
    • Ordinal data has a specific order, like ranks.
12. What is the purpose of data handling?
    • Data handling involves storing and managing data safely.
13. Name an example of information.
    • A student ID card is an example of information.
14. What is a source of information?
    • The internet is a source of information.
15. What is the difference between data and information?
    • Data is unprocessed, while information is processed and meaningful.

Evaluation

1. Define data in simple terms.
   • Data are raw, unprocessed facts.
2. State any two characteristics of good information.
   • Good information is reliable and accurate.
3. What is the difference between qualitative and quantitative data?
   • Qualitative data is descriptive, while quantitative is numerical.
4. List two sources of data.
   • Television and the internet.
5. Explain what continuous data means.
   • Continuous data can take any value within a specified range.
6. Differentiate between interval data and ratio data.
   • Interval data lacks a true zero, while ratio data includes a true zero.
7. What is discrete data?
   • Discrete data is whole and countable, like number of students.
8. Give an example of nominal data.
   • Gender is an example of nominal data.
9. Mention any two examples of information.
   • A student ID card and a utility bill.
10. What is data visualization?
    • Data visualization is the representation of data using visual tools like charts.

Conclusion

The teacher concludes by summarizing the topic and checking students’ notes to ensure correct understanding. Necessary corrections are provided as needed.