Question 1

Fuzzy matching is a data approach used to identify similar individuals based on data known about them.

Accepted Answer

False

Question 2

Alibaba and its attempt to identify seller and customer fraud based on various characteristics known about them is an example of similarity matching.

Accepted Answer

Alibaba using various characteristics to identify seller and customer fraud is an example of similarity matching.

Question 3

A decision tree can be used to divide data into smaller groups.

Accepted Answer

A decision tree is a hierarchically branched system that can be used to separate large datasets into smaller subsets based on certain criteria or rules. These branches or splits in the tree represent the decision points that help to divide the data into more specific groups or categories. Therefore, a decision tree is useful in dividing data into smaller groups.

Question 4

The P in IMPACT Cycle represents performing test plan.

Accepted Answer

The P in IMPACT Cycle represents planning and not performing test plan.

Question 5

Regression is a data approach used to estimate or predict,for each unit,the numerical value of some variable using some type of statistical model.

Accepted Answer

That is the definition of regression analysis.

Question 6

Clustering is a data approach used to divide individuals into groups in a useful or meaningful way.

Accepted Answer

Clustering is a data approach in which individuals are grouped together in a way that is useful or meaningful. This approach is often used in data mining and machine learning to identify patterns in large datasets. Clustering algorithms can be used to group similar individuals together based on their characteristics or behaviors, allowing researchers to better understand the underlying structure of the data.

Question 7

An example of classification would be a credit card company flagging a transaction as being approved or potentially being fraudulent and denying payment.

Accepted Answer

The credit card company uses classification to flag transactions as approved or potentially fraudulent, which is an example of binary classification.

Question 8

The data approach used to characterize the typical behavior of an individual,group or population by generating summary statistics about the data is referred to as classification.

Accepted Answer

The answer of The data approach used to characterize the...

Question 9

Link prediction is a data approach used to estimate or predict,for each unit,the numerical value of some variable using some type of statistical model.

Accepted Answer

Link prediction is used to predict the likelihood of a future association or link between two nodes in a network, not to estimate a numerical value of a variable.

Question 10

Benford's Law is an absolute and all data must conform.

Accepted Answer

While Benford's Law can be a useful tool for identifying potential fraud or errors in data sets, it is not an absolute law. There may be legitimate reasons for data to deviate from the expected distribution, such as deliberate manipulation or errors in data collection. Additionally, Benford's Law is most applicable to data sets that span several orders of magnitude, and may not hold true for small data sets.

Question 11

Data reduction is a data approach used to reduce the amount of information that needs to be considered to focus on the most critical items.

Accepted Answer

Data reduction involves filtering and summarizing large amounts of data to focus on the most important information. This approach can help save time and resources by avoiding the need to consider irrelevant or low-priority data.

Question 12

Fuzzy matching is a computer-assisted technique of finding matches that are less than 100 percent perfect by finding correspondences between portions of the text of each potential match.

Accepted Answer

This is the definition of fuzzy matching, which involves finding matches that are not identical but have similarities.

Question 13

When considering a question such as "Do our customers form natural groups based on similar attributes?" you would use an unsupervised approach.

Accepted Answer

Unsupervised learning is often used to identify patterns or groups in data without prior knowledge of what those patterns or groups might be. In this case, we do not have a pre-defined set of attributes or labels that we are trying to predict, so an unsupervised approach is appropriate.

Question 14

XBRL is used to facilitate the exchange of financial reporting information between the company and the Securities and Exchange Commission.

Accepted Answer

XBRL (eXtensible Business Reporting Language) is a standardized language used for the electronic communication of financial data. It is specifically designed for sharing financial data across different information systems, including between companies and regulatory bodies like the SEC. Therefore, it is true that XBRL is used to facilitate the exchange of financial reporting information between the company and the SEC.

Question 15

Data profiling typically involves unstructured data.

Accepted Answer

Data profiling involves structured data, which is organized and formatted in a specific way, in order to identify patterns and gain insights into the data. Unstructured data, on the other hand, refers to data that does not have a specific format or organization, such as text files, audio recordings, or images.

Question 16

XBRL is a global standard for exchanging financial reporting information that uses XML.

Accepted Answer

XBRL is indeed a global standard for exchanging financial reporting information and it does use XML (eXtensible Markup Language).

Question 17

A target is a manually assigned category applied to a record based on an event.

Accepted Answer

A target in the context of data or event processing typically refers to the intended outcome or goal of an action, rather than a manually assigned category. Categories applied to records based on events are more accurately described as labels or tags, which are used for classification or organization purposes.

Question 18

Co-occurrence grouping is an example of a supervised approach.

Accepted Answer

Co-occurrence grouping is an example of an unsupervised approach, as it involves finding patterns or relationships in data without the use of pre-existing labels or categories. Supervised approaches, on the other hand, rely on labeled data to learn patterns and make predictions or classifications.

Question 19

Existing data that has been manually evaluated and assigned a class is often referred to as test data.

Accepted Answer

Existing data that has been manually evaluated and assigned a class is typically referred to as labeled data, which is used for training and testing machine learning models. Test data specifically refers to a subset of data used to evaluate the performance of a model after it has been trained.

Question 20

Co-occurrence grouping could be used to match vendors by geographic region.

Accepted Answer

Co-occurrence grouping can be used to identify patterns and relationships between items, including vendors and their associated geographic regions. By analyzing the frequency of vendor and region co-occurrence, it is possible to group vendors by their geographic location, which can be useful for supply chain management or targeted marketing.

Quiz 3: Modeling and Evaluation: Going From Defining Business Problems and Data Understanding to Analyzing Data and Answering Questions