Data and Information

Definition of Data

Data refers to raw facts, figures, words, and symbols that have not been processed or organized into a meaningful form. Think of data as the raw material from which information is produced.

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Types of Data

Data can be broadly categorized into two main types:

1. Quantitative Data
2. Qualitative Data

Quantitative Data

Quantitative data are data that can be counted or measured, and are always given a numerical value.

Examples of Quantitative Data:

• Mobile numbers (e.g., 2348012345678, 2349098765432)
• Scores of tests and exams (e.g., 74.5, 67, 98)
• The weight of a person (e.g., 59.5kg, 88kg)
• The temperature in a room (e.g., 31°C, 26°C)

Types of Quantitative Data

1. Discrete data: This type of data can be counted and has finite, distinct values. They are usually whole numbers.
   Examples: Number of students in a class (25), number of cars in a parking lot (120).
2. Continuous data: Continuous data can assume any value within a given range. They have infinite possible values and can often involve decimals or fractions.
   Examples: A person's height (1.75m), temperature (36.8°C), time (10.25 seconds).

Qualitative Data

Qualitative data are data that cannot be expressed as a number and therefore cannot be measured numerically. It mainly consists of words, pictures, symbols, or descriptions. It is also known as Categorical Data because the information can be sorted into categories rather than by numerical value.

Examples of Qualitative Data:

• Colors (e.g., Red, Blue, Green)
• Names of countries (e.g., Switzerland, New Zealand, South Africa, Nigeria)
• Ethnicity (e.g., American Indian, Asian, African, European)
• Favorite types of music (e.g., Pop, Jazz, Fuji)

Types of Qualitative Data

1. Nominal Data: The term 'nominal' comes from the Latin word "nomen," meaning 'name'. This data type is used purely for labeling or naming variables, without implying any quantitative value or order.
   Examples of Nominal Data:
   • Gender (Women, Men)
   • Hair colour (Blonde, Brown, Black, Red)
   • Marital status (Married, Single, Widowed, Divorced)
   • Types of fruits (Apple, Banana, Orange)
2. Ordinal Data: "Ordinal" means "order". This type of qualitative data places variables in a rank or specific order, but the differences between the ranks may not be equal or quantifiable.
   Examples of Ordinal Data:
   • Educational levels (Primary, Secondary, Tertiary)
   • Customer satisfaction ratings (Very Dissatisfied, Dissatisfied, Neutral, Satisfied, Very Satisfied)
   • Finishing positions in a race (First, Second, Third)
   • Socio-economic status (Low, Medium, High)

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Sources of Data

Data can be gathered or collected from various sources, depending on the type of information needed. Some common sources include:

1. Federal Office of Statistics (e.g., for population, economic data)
2. National Population Commission (e.g., census data, birth/death records)
3. Independent National Electoral Commission (INEC) (e.g., voter registration data, election results)
4. Examination Bodies (e.g., WAEC, NECO for student academic performance)
5. School Attendance Registers (e.g., for student presence records)
6. Bank Statements (e.g., for financial transaction data)
7. Surveys and Questionnaires
8. Observations

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Definition of Information

Information is processed data. It can also be defined as knowledge gained about a particular fact or circumstance that has been organized and made meaningful. Information provides context and allows for understanding and decision-making.

Sources of Information

Information can be obtained from different sources, both traditional and modern. Some common sources of information include the following:

1. Radio
2. Television
3. Newspapers and Magazines
4. Computer and the Internet (e.g., websites, online databases)
5. Books and Journals
6. Discussions and Interviews

Qualities of Good Information

For information to be valuable and effective, it should possess the following key qualities:

1. Relevance: The information must be suitable and directly applicable for the purpose it is required for. Irrelevant information is useless.
2. Accuracy: It must be free from errors, complete, and correct. Inaccurate information can lead to wrong decisions.
3. Availability: It should be easy to obtain or access when needed, without undue delay or difficulty.
4. Timely: It should be available at the right time. Information that is too old may no longer be useful.
5. Comprehensive/Completeness: It should contain all necessary details required to make a decision or understand a situation.
6. Reliability: It should come from a credible and trustworthy source. Unreliable information can be misleading.

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Processing of Converting Data into Information

The transformation of raw data into meaningful information involves a combination of activities and procedures. Some of the key steps include:

1. Collecting: This is the initial step where raw data to be processed is gathered from various sources.
2. Classifying: This is the process of identifying specific characteristics in an item of data and grouping them into categories based on those characteristics.
3. Sorting: Sorting involves arranging data into a predefined order or sequence, such as alphabetically, numerically, or chronologically.
4. Editing: This step focuses on correcting any mistakes, inconsistencies, or errors found within the collected data to ensure accuracy.
5. Calculating: This involves performing arithmetic manipulations (like adding, subtracting, dividing, and multiplying) or other mathematical operations on the data.
6. Translating: This is the process of changing the language, format, or representation of a piece of data into another, often to make it understandable or compatible with a system.

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Difference between Data and Information

Data	Information
1. Raw facts.	1. Processed data.
2. An unorganized array of elements.	2. Arranged elements.
3. Unanalyzed sets of elements.	3. Analyzed elements.
4. It often makes no meaning on its own.	4. It is meaningful and provides understanding.
5. Can be numeric, alphabetic, or alphanumeric.	5. Usually presented in a context that aids decision-making.

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Digitalization of Data

Prior to the digital age, data, records, and information were manually processed, stored, and preserved primarily on physical media such as paper documents, books, and journals. However, with the advent of computers and digital technology, data can now be stored, preserved, and quickly retrieved on digital media like hard disks, solid-state drives, flash drives, and CD-ROMs.

This digital approach offers significant advantages, including greater economy (saving physical space and cost), enhanced security (through encryption and backups), improved durability (less prone to physical damage), and superior efficiency (faster access and processing).

Definition of Digitalization of Information

Digitalization of Information is the process of transforming manual or physical data into a binary format or digital form, making it readable and processable by computers. This conversion allows for the numerous benefits of digital storage and processing.