M1

Question 1

[ ] are fundamental components in various fields, providing tools for data interpretation and decision-making.

Answer 1

Statistical analysis and Modeling (SAM)

Question 2

[ ] primarily focuses on the collection, analysis, interpretation, presentation, and organization of data.

Answer 2

Statistics

Question 3

[ ] provides foundational tools for understanding data distributions, variability, and relationships through methods such as hypothesis testing and regression analysis.

Answer 3

Statistics

Question 4

[ ] encompasses a broader scope, integrating statistical methods with advanced computational techniques to derive insights from data.

Answer 4

Analytics

Question 5

[ ] emphasizes predictive modeling, data mining, and the application of algorithms to inform strategic decisions and optimize processes.

Answer 5

Analytics

Question 6

A [ ] is an interlinked set of activities that an organization performs to convert inputs to outputs that are valuable to a market.

Answer 6

value chain

Question 7

Insights that prescribe direct and meaningful actions then [ ].

Answer 7

drive decision making

Question 8

When is the value of data to organizations and their market is realized?

Answer 8

When actions or decisions are implemented from them.

Question 9

What are the five main data sources?

Answer 9

(TransData - ContractSub - Surve - DataPool - Unstruct)
- Transactional Data
- Contractual, Subscription, or Account Data
- Surveys
- Data Poolers
- Unstructured Data

Question 10

This type of data source consists of structured, detailed information capturing the key characteristics of a transaction.

Answer 10

Transaction Data

Question 11

This type of data source includes information about the type of product combined with customer characteristics.

Answer 11

Contractual, Subscription, or Account Data

Question 12

This type of data source are questionnaires aimed at extracting sociodemographic and behavioral data from a particular group of people.

Answer 12

Surveys

Question 13

These are companies that gather data in particular settings or for particular purposes and sell them to interested customers looking to enrich or extend their data sources.

Answer 13

Data Poolers

Question 14

This refers to information that does not reside in a traditional row-column database in the world of big data.

Answer 14

Unstructured Data

Question 15

What are the phases of Data Analytics?

Answer 15

(Bu - Du - Dp - M - E - D)
- Business Understanding
- Data Understanding
- Data Preparation
- Modelling
- Evaluation
- Deployment

Question 16

[ ] is knowing what the study is for or identifying a business task.

Answer 16

Business Understanding

Question 17

[ ] is when you select the related data from many available databases to correctly describe a given business task; identifying relevant data for the problem description.

Answer 17

Data Understanding

Question 18

[ ] is also known as data preprocessing.

Answer 18

Data Preparation

Question 19

[ ] is to filter, aggregate, and fill-in (impute) missing values.

Answer 19

Data Preparation

Question 20

[ ] uses mathematical formulations to convert different measurements into a unified numerical scale.

Answer 20

Data Transformation

Question 21

Transforming numerical to numerical scales [ ].

Answer 21

shrinks or enlarges the data

Question 22

Transforming categorical to numerical values can be [ ].

Answer 22

ordinal (less, moderate, strong) or nominal (red, yellow, blue).

Question 23

What are the two major categories of modeling?

Answer 23

• Predictive Modeling
• Descriptive Modeling

Question 24

[ ] predicts the value of an attribute based on the values of other attributes.

Answer 24

Predictive Modeling

Question 25

[ ] derives patters that summarizes the underlying relationships in the data.

Answer 25

Descriptive Modeling

Question 26

[ ] summarizes the general characteristics or features of a target class of data.

Answer 26

Characterization

Question 27

What are the methods of Characterization and Discrimination?

Answer 27

• data summaries based on stat measures and plots.
• user-controlled data summarization using OLAP, EXCEL, Spreadsheet, SQL, Python, etc.

Question 28

What are the outputs of Characterization and Discrimination?

Answer 28

• pie charts, bar charts, curves, crosstabs
• Characteristic Rules

Question 29

[ ] compares the general features of the target class data objects against the general features of objects from one or multiple contrasting classes.

Answer 29

Discrimination

Question 30

[ ] is the process of finding a model or function that describes and distinguishes classes or concepts.

Answer 30

Classification

Question 31

[ ] is a statistical methodology that is most often used for numeric prediction.

Answer 31

Regression Analysis

Question 32

[ ] is when objects are grouped based on the principle of maximizing the intraclass similarity and minimizing the interclass similarity.

Answer 32

Clustering

Question 33

[ ] detects objects in data that do not follow norms and its methods may include statistical tests or using distance measures.

Answer 33

Outlier Analysis

Question 34

What are the two things to consider in the Data Interpretation stage?

Answer 34

• How to recognize business value from knowledge patters discovered.
• How to visualize the results to properly interpret patterns.

Question 35

A pattern is interesting if:

Answer 35

• easily understood by humans
• valid on new or test data with some degree of certainty
• potentially useful
• novel

Question 36

What are the two primary techniques of descriptive analytics?

Answer 36

• Data Aggregation
• Data Presentation