Question 1

A common example of interval scale measurement is temperature on the Celsius scale.

Accepted Answer

Temperature on the Celsius scale is an example of interval scale measurement because the intervals between the numbers are equal and meaningful, but there is no true zero point.

Question 2

The data mining environment is usually a client-server architecture or a Web-based information systems architecture.

Accepted Answer

The data mining environment can be a client-server architecture or a Web-based information systems architecture.

Question 3

Associations are a type of pattern that discovers time-ordered events, such as predicting that an existing banking customer who already has a checking account will open a savings account followed by an investment account within a year.

Accepted Answer

Associations in data mining are used to find patterns that describe items that often occur together, but they do not inherently involve time-ordered events. Sequence or time-series analysis would be more appropriate for predicting time-ordered events.

Question 4

Predictions tell the nature of future occurrences of certain events based on what has happened in the past, such as predicting the winner of the Super Bowl or forecasting the absolute temperature of a particular day.

Accepted Answer

Predictions are typically based on past events and data patterns to make an estimation of what will happen in the future.

Question 5

Technically speaking, data mining is a process that uses statistical, mathematical, and artificial intelligence techniques to extract and identify useful information and subsequent knowledge from large sets of data.

Accepted Answer

Data mining involves using various techniques to analyze and extract insights from large datasets. These techniques may include statistics, machine learning, and other artificial intelligence methods. The ultimate goal is to identify patterns, trends, and correlations in the data that can help inform business decisions or guide future research.

Question 6

Mass, length, time, plane angle, energy, and electric charge are examples of physical measures whose data are represented in interval scales.

Accepted Answer

Mass, length, time, plane angle, energy, and electric charge are examples of physical measures whose data are represented in ratio scales, not interval scales, because they have a meaningful zero point that allows for the comparison of absolute magnitudes.

Question 7

Data mining is a prime candidate for better management of companies that are data-rich, but knowledge-poor.

Accepted Answer

Data mining involves extracting valuable insights from large data sets, making it an ideal technique for companies that have a wealth of data but lack the knowledge to effectively analyze it. By leveraging data mining techniques, these companies can identify patterns, trends, and insights that can inform better decision-making and improve their overall business performance.

Question 8

Data types such as date/time, unstructured text, image, and audio need to be converted into some form of categorical or numeric representation before they can be processed by data mining algorithms.

Accepted Answer

This statement is true. Data mining algorithms typically require categorical or numeric data as input, meaning that data types such as date/time, unstructured text, image, and audio need to be converted into a format that can be processed.

Question 9

In order to be applied successfully, a data mining study must be viewed as a set of automated software tools and techniques.

Accepted Answer

Data mining success relies not only on the use of automated tools and techniques but also on the understanding of the domain, data interpretation, and integration with decision-making processes.

Question 10

At the highest level of abstraction, all data can be divided into interval data and ratio data.

Accepted Answer

At the highest level of abstraction, all data can be divided into two main categories: qualitative (or categorical) data and quantitative (or numerical) data. Interval data and ratio data are subcategories of quantitative data.

Question 11

Data mining offers organizations a decision-enhancing environment to exploit opportunities by transforming data into a strategic weapon.

Accepted Answer

Data mining enables organizations to extract valuable insights from their data, which can then be used to inform strategic decision making and gain a competitive advantage. By leveraging data as a strategic weapon, organizations can identify market trends, customer preferences, and operational inefficiencies that would otherwise go unnoticed.

Question 12

Cross-Industry Standard Process for Data Mining, or CRISP-DM, is one of the most popular
nonproprietary standard methodologies for data mining.

Accepted Answer

CRISP-DM is indeed one of the most popular nonproprietary standard methodologies for data mining.

Question 13

Newer Web-based tools enable managers at all educational levels to do data mining.

Accepted Answer

Newer Web-based tools do indeed enable managers at all educational levels to do data mining.

Question 14

The first step in the data mining process is to understand the relevant data from the available databases.

Accepted Answer

The answer of The first step in the data mining...

Question 15

Two types of categorical data are nominal data and ordinal data.

Accepted Answer

Nominal data are categorical data that cannot be arranged in any particular order, while ordinal data are categorical data that can be arranged in a particular order.

Question 16

Compared to the other steps in CRISP-DM, data preprocessing consumes the most time and effort; most believe that this step accounts for roughly 80 percent of the total time spent on a data mining project

Accepted Answer

Data preprocessing involves tasks such as cleaning, integration, transformation, and reduction of data, which are time-consuming and require significant effort. It is considered the most important and time-consuming step in the CRISP-DM process.

Question 17

The variable marital status can be categorized using the codes (1) single, (2) married, and (3) divorced. These codes are examples of ordinal data.

Accepted Answer

The codes for marital status have an order or sequence. Single (1) is considered the lowest category, followed by married (2), and then divorced (3). Therefore, this is an example of ordinal data.

Question 18

Data mining is a way for companies to develop business intelligence from their data to gain a better understanding of their customers and operations and to solve complex organizational problems.

Accepted Answer

Data mining involves using software tools and algorithms to analyze large amounts of data and identify patterns and relationships that can be useful for business decision-making. By discovering insights from their data, companies can improve their decision-making capabilities, optimize their operations, and create more targeted and effective marketing campaigns.

Question 19

Data mining requires a separate, dedicated database.

Accepted Answer

Data mining can be performed on existing databases without the need for a separate one. However, some organizations may choose to create a separate dedicated database for data mining purposes.

Question 20

Clustering partitions a collection of things, such as objects and events presented in a structured dataset into segments whose members share similar characteristics.

Accepted Answer

This statement accurately describes what clustering does by grouping similar items or events together based on certain characteristics.

Quiz 4: Data Mining for Business Intelligence