Data Management :Types of Data, Data Collection Methods And Tools Assignment

Types of Data

Qualitative data Versus Quantitative Data

Quantitative Data

• Discrete Data
• Continuous Data

Guess if the following are Qualitative or Quantitative data

• Gender
• Test results
• Customer satisfaction

Suggest more examples of data to this list and let’s discuss their type.

Qualitative Data

• Nominal Data
• Ordinal Data

Nominal data

This is also called naming data. This is a type that names or labels the data, and its characteristics are similar to a noun.

Example: person’s name, gender, school name.

Questions to gather nominal data look like:

• What is your name?
• What is your pet’s name?

Ordinal data

This includes data or elements of data that is ranked, ordered or used on a rating scale. You can count and order ordinal data but it doesn’t allow you to measure it.

Example: Seminar attendants are asked to rate their seminar experience on a scale of 1-5. Against each number, there will be options that will rate their satisfaction like “very good, good, average, bad, and very bad”.

Sequential data

• Sequential Data is any kind of data where the order matters.
• Examples of sequence data include DNA, stock price, customer purchase history, weather.

Random data

• The term random refers to any collection of data or information with no determined order or is chosen in a way that is unknown beforehand.

Example

• Rolling a dice gives you random numbers, 1,2,3,4,5 or 6.

Categorical data

• Categorical data represent types of data which may be divided into groups. Examples of categorical data are race, gender, age group, and educational level.
• The data collected in the categorical form is also known as qualitative data. Each dataset can be grouped and labelled depending on their matching qualities, under only one category. This makes the categories mutual exclusive

Numerical data

Numerical data refers to the data that is in the form of numbers, and not in any language or descriptive form.

Often referred to as quantitative data, numerical data is collected in number form and stands different from any form of number data types due to its ability to be statistically and arithmetically calculated.

Discrete data

• Discrete data is used to represent countable items. It can take both numerical and categorical forms and group them into a list. This list can be finite or infinite too.
• Discrete data basically takes countable numbers like 1, 2, 3, 4, 5, and so on. In the case of infinity, these numbers will keep going on.

Example: counting ice cubes from an ice tray is finite countable. But counting ice cubes from all over the world is infinite countable.

Continuous data

As the name says, this form has data in the form of intervals.

Or simply said ranges. Continuous numerical data represent measurements, and their intervals fall on a number line.

Hence, it doesn’t involve taking counts of the items.

Example: in a school exam, students who scored 80%-100% come under distinction, 60%-80% have first-class and below 60% are second class.

Data collection methods/Tools

• Surveys
• Interviews
• Focus group discussions
• Open ended questions
• Social media platform
• Authorized mechanisms(registration, exams results , documents, reports)

Data collection methods

• Nominal data àopen-ended questions
• Ordinal data àmultiple-choice questions
• Discrete and continuous dataàMostly collected through multiple-choice questions and sometimes through open-ended questions.

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