Chapter 8

Question 1

Quantitative analysis

Answer 1

focuses on quantifying the patterns and correlations found in the data
technique involves analyzing a large number of observations from a dataset
Quantitative analysis results are absolute in nature and can therefore be used for numerical comparisons

Question 2

Qualitative analysis

Answer 2

-focuses on describing various data qualities using words
-smaller sample in greater depth compared to
quantitative data analysis
-They also cannot be measured numerically or used for
numerical comparisons.

Question 3

Data mining

Answer 3

–data discovery, is a specialized form of data analysis that
targets large datasets
–refers to automated, software-based techniques that sift through massive datasets to identify patterns and trends.
–extracting hidden or unknown patterns in the data with the
intention of identifying previously unknown patterns
–Data mining forms the basis for predictive analytics and business intelligence (BI).

Question 4

Statistical Analysis

Answer 4

Statistical analysis uses statistical methods based on mathematical formulas as a means for
analyzing data.
is most often quantitative, but can also be qualitative

Question 5

A/B Testing

Answer 5

known as split or bucket testing, compares two versions of an element to determine which version is superior based on a pre-defined metric.

Question 6

Correlation

Answer 6

an analysis technique used to determine whether two variables are related to each other

• The use of correlation helps to develop an understanding of a dataset and find relationships that can assist in explaining a phenomenon.
• Correlation is therefore commonly used for data mining where the identification of relationships between variables in a dataset leads to the discovery of patterns and anomalies.

Question 7

Regression

Answer 7

explores how a dependent variable is related to an independent variable within a dataset.

Question 8

Classification (Supervised Machine Learning)

Answer 8

supervised learning technique by which data is classified into relevant, previously learned categories.
It consists of two steps:
1. The system is fed training data that is already categorized or labeled, so that it can develop an understanding of the different categories.
2. The system is fed unknown but similar data for classification and based on the understanding it developed from the training data, the algorithm will classify the unlabeled data.

Question 9

Clustering (Unsupervised Machine Learning)

Answer 9

Clustering is an unsupervised learning technique by which data is divided into different groups so that the data in each group has similar properties.
There is no prior learning of
categories required. Instead, categories are implicitly generated based on the data groupings.
Clustering is used in data mining

Question 10

Outlier Detection

Answer 10

process of finding data that is significantly different from or
inconsistent with the rest of the data within a given dataset.
-This machine learning technique is used to identify anomalies, abnormalities and deviations that can be advantageous, such as opportunities, or unfavorable, such as risks.
-Outlier detection is closely related to the concept of classification and clustering, although its algorithms focus on finding abnormal values. It can be based on either supervised or unsupervised learning

Question 11

Filtering

Answer 11

Filtering is the automated process of finding relevant items from a pool of items

Question 12

Filtering is generally applied via the following two approaches

Answer 12

• collaborative filtering

* content-based filtering

Question 13

Collaborative filtering

Answer 13

Collaborative filtering is an item filtering technique based on the collaboration, or merging, of a user’s past behavior with the behaviors of others. A target user’s past behavior, including their likes, ratings, purchase history and more, is collaborated with the
behavior of similar users. Based on the similarity of the users’ behavior, items are filtered for the target user.
–solely based on the similarity between users’ behavior.
–large amount of user behavior data in order to accurately filter items

Question 14

Content-based filtering

Answer 14

an item filtering technique focused on the similarity between users and items

Question 15

Natural language processing

Answer 15

computer’s ability to comprehend human speech and text as naturally understood by humans

Question 16

Sentiment analysis

Answer 16

Sentiment analysis is a specialized form of text analysis that focuses on determining the bias or emotions of individuals.