Data and Information
Definition of Data
Types of Data
2. Qualitative Data
Quantitative Data
Examples of quantitative data are given below:
Mobile number E.g. 23483873385, 235976768878
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° 26°
Types of Quantitative Data
a. Discrete data: Data that can be counted and has finite values is known as discrete data. Examples: 1, 2, 50, 89b. Continuous data: Continuous data are data which can assume any value. They have infinite values. Examples: 1.33, 0.222, 45.11111
Qualitative Data
Examples of qualitative data:
Colors
Names of countries such as Switzerland, New Zealand, South Africa, etc.
Ethnicity such as American Indian, Asian, etc.
Types of Qualitative Data
a. Nominal Data:The term ‘nominal’ comes from the Latin word “nomen” which means ‘name’. This data type is used just for labelling or naming variables, without having any quantitative value.Examples of Nominal Data:
Gender (Women, Men)
Hair colour (Blonde, Brown, Brunette, Red, etc.)
Marital status (Married, Single, Widowed)
b. Ordinal Data: “Ordinal” means “order”. This type of qualitative data places variables in rank or order. Examples of Ordinal Data: First, second, and third, etc, low, medium, and high.
Sources of data
i. Federal Office of Statistics
ii. National Population Commission
iii. Independent Electoral Commission
iv. Examination Bodies
v. School attendance Register
vi. Bank Statement
Definition of Information
Information is processed data. It can also be defined as knowledge gained about a particular fact or circumstance.
Sources of information
i. Radio
ii. Television
iii. Newspaper
iv. Computer
Qualities of good information
b. Accurate: It is free from errors
c. Availability: It should be easy to obtain or access
d. Timely: It should be available at the right time
e. Comprehensive/Completeness: It should contain all necessary details
f. Reliability: It should come from a reliable source.
Processing of Converting Data into Information
i. Collecting: Data to be processed need to be gathered from various sources
ii. Classifying: This is the process of identifying certain characteristics in an item of data and putting them into categories or groups according to those characteristics
iii. Sorting: Sorting takes the form of arranging data into a predefined order of sequence.
iv. Editing: This takes the form of correcting mistakes from the body of data.
v. Calculating: This is by performing arithmetic manipulation such as adding, subtracting, dividing and multiplication
vi. Translating: This is the process of changing the language form of a piece of data into another.
Difference between Data and Information
Data | Information |
---|---|
1. Raw facts | 1. Processed data |
2. An unorganized array of elements | 2. Arranged element |
3. Unanalyzed sets of element | 3. Analyzed element |
4. It makes no meaning | 4. It is meaningful |
Digitalization of Data
Prior to the digital age, data, records, and information were manually processed, stored, and preserved on paper, books, and journals. However, with the advent of computers, data can now be stored, preserved, and quickly retrieved on digital media such as hard disks, flash drives, and CD-ROMs. This digital approach offers greater economy, security, durability, and efficiency.
Given the advantages of the digital era, it is beneficial to convert data that was previously processed and stored manually or physically into digital or binary form.
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