Week 4 Data Types

Data types in Insurance domain -

  1. Qualitative (Nominal) - Race of Policy Holders like Asian, African etc
  2. Qualitative (Ordinal) - Underwriting Risk like High risk, medium, low etc.
  3. Quantitative (Discrete) - Number of policies sold in a year
  4. Quantitative (Continuous) - Premium amount collected in a year

Banking domain:

  1. Nominal: Checking, Savings
  2. Ordinal: Preferred Rewards Gold, Preferred Rewards Platinum, Preferred Rewards Honors Platinum
  3. Discrete: Number of accounts a customer holds in a bank
  4. Continuous: Interest earned on credit card purchases during holiday season.

Automotive car sales domain:

  1. Nominal - Eg. car color, features (AC, sunroof, alloys)
  2. Ordinal - Eg. variant choice (low, mid, top end)
  3. Discrete - Eg. # of accessories used, warranty package (2, 3, 4 years)
  4. Continuous - Eg. Road tax %, on road price, insurance value.

Automotive car service domain:

  1. Nominal - Eg: Periodic maintenance or accidental repair or breakdown maintenance
  2. Ordinal - Eg: Service experience rating (Excellent, Good, Average, Poor, Very Poor)
  3. Discrete - Eg: Service interval (every 10k kms), service occurrence (1st or 2nd or 3rd service)
  4. Continuous - Eg. Service cost, labor rate, material cost.
1 Like


Qualitative Data:

  1. Nominal: names of courses offered
  2. Ordinal: ratings on courses offered

Quantitative Data:

  1. Discrete: no. of students in a particular course
  2. Continuous: percentage change in the no. of students enrolled in a particular course
1 Like

HealthCare Domain:
Nominal : Gender of patients having diabetes.
Ordinal : Sugar levels of patients - risky low, low, normal, high, risky high
Discrete : Number of patients admitted per month for a year
Continuous : Blood Pressure of patients with heart attack

1 Like

For Government - Democracy and Growth
Some of the data attributes -

  1. Qualitative(Nominal) - Different Parties (BJP, Congress, BJD, RJD, etc)
  2. Qualitative(Ordinal) - Ruling, Opposition, Independent
  3. Quantitative(Discrete) - Portfolio (Home, Finance, Railway, External affairs, etc)
  4. Quantitive(Continuous) - Percentage of votes, World value survey, GDP growth, FDI investment, etc
1 Like

In Nominal - Do you mean “Type of Accounts”?

1 Like

Please provide more clarifications on some of your responses.

Example: Qualitative (Ordinal) - Ruling, Opposition and Independent - appear to be Nominal and not Ordinal. Just like different parties, these can be taken as different roles played by elected members. A better example can be a survey on how happy the citizens are with the performance of the government - A rating from 1 to 5 where 1 is Unsatisfactory to 5 being Excellent.

Example: Quantitative(Discrete) - Portfolio (Home, Finance, Railway, etc) - Again the way it has been described appears to be more like a Nominal data rather than Discrete. If you word it as Number of members working in each Portfolio (Home, Finance etc) - then it becomes a better example of Quantitative(Discrete).

1 Like

education domain:
if we consider that a particular college has MHRD ranking of 123, is the attribute MHRD rank discrete or ordinal?

Banking Domain


Account Holder
Account Number
Accounting Transaction
Account Type
Date of Transaction

Account Status
Loyalty status

No. of accounts

Account Balances
Interest rate
Transaction Amount



Vehicle Model
Vehicle Colour
Vehicle Manufacturing date
Vehicle Type

Vehicle Status
Vehicle Size

Sales per day
Sales per month

Vehicle Price
Loan interest