Data Types and Datasets in Data Science

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Questions and Answers

What distinguishes asymmetric binary variables from symmetric binary variables?

They can only take on discrete values.
They have unequal importance assigned to the choices. (correct)
They are always related to nominal data.
They have equal importance assigned to both choices.

Which of the following is an example of an ordinal variable?

Temperature measured in degrees Celsius.
Medical test results of positive and negative.
Shirt size with categories S, M, L, XL. (correct)
Gender with categories male and female.

What operations can typically be performed on ordinal data?

All arithmetic operations.
Mode and median calculations.
Only relational comparisons.
Both B and C. (correct)

In a binary variable related to medical testing, what convention is often used?

Positive outcome is assigned the highest numerical value. (B) Signup and view all the answers

What is one consequence of transforming a numerical variable into an ordinal variable?

Loss of some original data details. (D) Signup and view all the answers

Which scale of measurement is used for variables that have a true zero point?

Ratio scale (B) Signup and view all the answers

What is a characteristic of nominal data?

It represents categories without a defined order. (C) Signup and view all the answers

Which of the following datasets falls under relational records?

Relational tables (D) Signup and view all the answers

Which type of data can be described with the operations of addition and subtraction?

Quantitative data (D) Signup and view all the answers

An example of a binary nominal scale is?

Gender (male or female) (B) Signup and view all the answers

Which data type is represented by a term-frequency vector of text documents?

Document data (C) Signup and view all the answers

What distinguishes ordinal scales from nominal scales?

Ordinal scales can be ranked while nominal scales cannot. (C) Signup and view all the answers

Which of the following properties is NOT associated with quantitative data?

Categorization (B) Signup and view all the answers

What is a characteristic of interval data?

It can undergo multiplication by a constant. (B) Signup and view all the answers

Which of the following is an example of interval data?

Temperature in Celsius (B) Signup and view all the answers

What operation can be performed on interval data?

Subtraction of values (C) Signup and view all the answers

Which scale of measurement has both equal intervals and a true zero?

Ratio scale (B) Signup and view all the answers

Discrete data is best described as data that can take:

Only certain individual values (B) Signup and view all the answers

Which type of data is classified as categorical (qualitative)?

Age groups (young, middle-aged, old) (D) Signup and view all the answers

What defines the interval scale in data measurement?

Only positive values and no true zero (D) Signup and view all the answers

In NOIR classification, which data type is considered numeric and continuous?

Interval data (A) Signup and view all the answers

What characterizes a nominal variable?

It takes values among mutually exclusive codes without logical order. (C) Signup and view all the answers

Which of the following is an example of a binary variable?

Switch with options ON and OFF (D) Signup and view all the answers

How many categories can a nominal variable have at minimum?

Two categories (B) Signup and view all the answers

What is the significance of numbers in nominal data?

They have no mathematical interpretation. (D) Signup and view all the answers

Which of the following is NOT a feature of a nominal scale?

Values have an intrinsic order. (C) Signup and view all the answers

What is an example of a nominal scale in everyday use?

Blood types: A, B, AB, O. (A) Signup and view all the answers

Which of the following best describes a ternary variable?

It must have at least three categories. (D) Signup and view all the answers

Which of these statements about nominal and binary scales is accurate?

Binary variables are a special case of nominal variables. (C) Signup and view all the answers

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Study Notes

Data Types and Datasets

Record Data: This type of dataset contains information organized as records, which can be relational, matrix, transaction, or document data.
Relational Records: Data is structured in relational tables, common in databases.
Data Matrix: Represents data in a numerical format or as a table of frequencies.
Transaction Data: Contains records of purchases, events, or other transactions.
Document Data: Text documents represented as term-frequency vectors (matrices) for analysis.
Graphs and Networks: This dataset represents relationships between entities using nodes and edges.

Data in Data Science

Entity: A specific item or object being analyzed.
Attribute: Measurable property of an entity.
Data (Measurement): Values obtained by measuring or observing attributes of an entity.

Data Categorization: NOIR Topology

Nominal Scale: Categorizes data using labels with no inherent order. Examples include gender, blood groups, and country codes.
- Binary: A nominal scale with two categories (e.g., ON/OFF, True/False). Binary scales can be symmetric (both categories have equal importance) or asymmetric (one category is more significant than the other).
Ordinal Scale: Categorizes data with a defined order between categories but without equal intervals. Examples include shirt sizes (S, M, L, XL), ranking positions, or levels of agreement (strongly disagree, disagree, ...).
Interval Scale: Categorizes data with equal intervals between values but no true zero point. Examples include temperature scales (Celsius, Fahrenheit) or dates.
Ratio Scale: Categorizes data with equal intervals and a true zero point. Examples include height, weight, or income.

Qualitative vs. Quantitative Data

Qualitative data: Categorical data that provides descriptions and insights.
Quantitative data: Numerical data that provides measurements and quantifiable information.

Properties of Data

Distinctiveness: Determines if two data points are equal or not. This applies to Categorical (Qualitative) data.
Order: Relates data points using greater than or less than operators. This applies to Categorical (Qualitative) data.
Addition: Allows data points to be combined using addition or subtraction. This applies to Numerical (Quantitative) data.
Multiplication: Allows data points to be combined using multiplication or division. This applies to Numerical (Quantitative) data.