D491 WGU INTRODUCTION TO ANALYTICS OA
EXAM QUESTIONS AND CORRECT DETAILED
ANSWERS (VERIFIED ANSWERS) |ALREADY
GRADED A+
Data Transformation - ANSWER>>Data mapping: converting data from one format
to another.
Data deduplication: eliminating repeated or redundant data.
Derived variables: creating new variables from existing ones.
Data sorting or ordering: arranging data in a specific sequence.
Data Transformation occurs in the ______ _____________ phase, the role this
applies to is the _____ A___ - ANSWER>>Preparation phase, Data Analyst
____________ is great at combining unstructured data feeds from multiple
sources. - ANSWER>>Hadoop
Examples of when to use _____ : stream processing, fraud detection, and
prevention, content management, risk management. - ANSWER>>Hadoop
Set up sandbox, extract and transform data, condition data and exploring visually
occurs in the ______ ____________ phase - ANSWER>>Data Preparation
When you convert a Microsoft Word file to a PDF, for example, you are
________data - ANSWER>>transforming
Running a virtual machine on Linux operating system on Windows is an example
of ---------- - ANSWER>>sandboxing
Some key features of an Analytical Sandbox may include tools and features for c---
------- and s---ing work with colleagues. Flexibility to allow analysts to try out
,different analytical approaches and techniques. Clear documentation and support
resources to help analysts get up to speed quickly. - ANSWER>>collaboration,
sharing
Why is it important to collect data in a certain time frame? - ANSWER>>Result:
more precise findings than working with an open-ended timeframe.
___ testing works by randomly showing two versions of the same asset (ad,
website, pop-up, offer, etc.) to different users - ANSWER>>A/B
What does it mean for a dependent variable to be binary?
(this is always applied to logistic regression) - ANSWER>>A binary variable is a
categorical variable that can only take one of two values, usually represented as a
Boolean — True or False — or an integer variable — 0 or 1, yes or no, sick or not
sick, obese or underweight, etc., depending on the independent variable.
______ Analysis when you're looking to segment or categorize a dataset into
groups based on similarities, but aren't sure what those groups should be. -
ANSWER>>Cluster Analysis
Preprocessing (of data) - ANSWER>>the process of transforming raw data into an
understandable format
Bounce Rate - ANSWER>>the percentage of visitors to a particular website who
navigate away from the site after viewing only one page.
Logistic Regression - ANSWER>>A statistical analysis which determines an
individual's risk of the outcome as a function of a risk factor. The outcome of
interest has two categories (yes or no, obese or not obese, at risk of cancer or not
at risk of cancer, happens or does not happen, etc.).
K-means clustering - ANSWER>>Informally, goal is to find groups of points that
are close to each other but far from points in other groups.
,• Each cluster is defined entirely and only by its centre, or mean value µk
Random Forest - ANSWER>>An algorithm used for regression or classification that
uses a collection of tree data structures trees "vote" on the best model.
Examples of when to use Random Forest - ANSWER>>In HC: to identify the
correct combination of components in medicine and to analyze a patient's
medical history to identify diseases (for example using symptoms to predict
whether a person's symptoms are more closely tied to malaria or a simple fever,
another example can be a cold or a sinus infection).
Centroid Clustering - ANSWER>>clusters are represented by their centroids.
hierarchical clustering with cluster distance defined by a centroid/assigned center
___ has many applications in diverse fields such as face recognition, computer
vision, image compression, bioinformatics, and fraud detection. - ANSWER>>PCA
Density Clustering - ANSWER>>detecting areas where points are concentrated
and where they are separated by areas that are empty or sparse.
Data Wrangling is - ANSWER>>the process of removing errors and combining
complex data sets to make them more accessible and easier to analyze.
Data Wrangling Examples - ANSWER>>Merging several data sources into one
data-set for analysis.
Identifying gaps or empty cells in data and either filling or removing them.
Deleting irrelevant or unnecessary data.
Identifying severe outliers in data and either explaining the inconsistencies or
deleting them to facilitate analysis.
Merging several data sources into one data-set for analysis.
Identifying gaps or empty cells in data and either filling or removing them.
Deleting irrelevant or unnecessary data.
, Identifying severe outliers in data and either explaining the inconsistencies or
deleting them to facilitate analysis. - ANSWER>>Data Wrangling Examples
Maintaining Databases examples/purpose - ANSWER>>Routines meant to help
performance, free up disk space, check for data errors, check for hardware faults,
update internal statistics, and many other obscure (but important) things.
Maintaining DB2® and Oracle databases involves updating statistics, monitoring
database, server, and space utilization, and planning backup and recovery
strategies. - an example of ? - ANSWER>>Maintaining databases
Project initiation falls under what role? - ANSWER>>Project Sponsor
How to find p-value? - ANSWER>>-look at alternative
-if less than, find area to the left of z value
-if greater than, find area to the right of z value
-if not equal to, if positive, find area to the right and double it. if negative, find
area to the left and double it.
creating tables and establishing relationships between those tables according to
rules designed both to protect the data and to make the database more flexible
by eliminating redundancy and inconsistent dependency. -
ANSWER>>normalization
OpenLayers - ANSWER>>
MATLAB - ANSWER>>The Matrix Laboratory language is used for a variety of
mathematical calculations and tasks
Ruby - ANSWER>>
Swift - ANSWER>>
EXAM QUESTIONS AND CORRECT DETAILED
ANSWERS (VERIFIED ANSWERS) |ALREADY
GRADED A+
Data Transformation - ANSWER>>Data mapping: converting data from one format
to another.
Data deduplication: eliminating repeated or redundant data.
Derived variables: creating new variables from existing ones.
Data sorting or ordering: arranging data in a specific sequence.
Data Transformation occurs in the ______ _____________ phase, the role this
applies to is the _____ A___ - ANSWER>>Preparation phase, Data Analyst
____________ is great at combining unstructured data feeds from multiple
sources. - ANSWER>>Hadoop
Examples of when to use _____ : stream processing, fraud detection, and
prevention, content management, risk management. - ANSWER>>Hadoop
Set up sandbox, extract and transform data, condition data and exploring visually
occurs in the ______ ____________ phase - ANSWER>>Data Preparation
When you convert a Microsoft Word file to a PDF, for example, you are
________data - ANSWER>>transforming
Running a virtual machine on Linux operating system on Windows is an example
of ---------- - ANSWER>>sandboxing
Some key features of an Analytical Sandbox may include tools and features for c---
------- and s---ing work with colleagues. Flexibility to allow analysts to try out
,different analytical approaches and techniques. Clear documentation and support
resources to help analysts get up to speed quickly. - ANSWER>>collaboration,
sharing
Why is it important to collect data in a certain time frame? - ANSWER>>Result:
more precise findings than working with an open-ended timeframe.
___ testing works by randomly showing two versions of the same asset (ad,
website, pop-up, offer, etc.) to different users - ANSWER>>A/B
What does it mean for a dependent variable to be binary?
(this is always applied to logistic regression) - ANSWER>>A binary variable is a
categorical variable that can only take one of two values, usually represented as a
Boolean — True or False — or an integer variable — 0 or 1, yes or no, sick or not
sick, obese or underweight, etc., depending on the independent variable.
______ Analysis when you're looking to segment or categorize a dataset into
groups based on similarities, but aren't sure what those groups should be. -
ANSWER>>Cluster Analysis
Preprocessing (of data) - ANSWER>>the process of transforming raw data into an
understandable format
Bounce Rate - ANSWER>>the percentage of visitors to a particular website who
navigate away from the site after viewing only one page.
Logistic Regression - ANSWER>>A statistical analysis which determines an
individual's risk of the outcome as a function of a risk factor. The outcome of
interest has two categories (yes or no, obese or not obese, at risk of cancer or not
at risk of cancer, happens or does not happen, etc.).
K-means clustering - ANSWER>>Informally, goal is to find groups of points that
are close to each other but far from points in other groups.
,• Each cluster is defined entirely and only by its centre, or mean value µk
Random Forest - ANSWER>>An algorithm used for regression or classification that
uses a collection of tree data structures trees "vote" on the best model.
Examples of when to use Random Forest - ANSWER>>In HC: to identify the
correct combination of components in medicine and to analyze a patient's
medical history to identify diseases (for example using symptoms to predict
whether a person's symptoms are more closely tied to malaria or a simple fever,
another example can be a cold or a sinus infection).
Centroid Clustering - ANSWER>>clusters are represented by their centroids.
hierarchical clustering with cluster distance defined by a centroid/assigned center
___ has many applications in diverse fields such as face recognition, computer
vision, image compression, bioinformatics, and fraud detection. - ANSWER>>PCA
Density Clustering - ANSWER>>detecting areas where points are concentrated
and where they are separated by areas that are empty or sparse.
Data Wrangling is - ANSWER>>the process of removing errors and combining
complex data sets to make them more accessible and easier to analyze.
Data Wrangling Examples - ANSWER>>Merging several data sources into one
data-set for analysis.
Identifying gaps or empty cells in data and either filling or removing them.
Deleting irrelevant or unnecessary data.
Identifying severe outliers in data and either explaining the inconsistencies or
deleting them to facilitate analysis.
Merging several data sources into one data-set for analysis.
Identifying gaps or empty cells in data and either filling or removing them.
Deleting irrelevant or unnecessary data.
, Identifying severe outliers in data and either explaining the inconsistencies or
deleting them to facilitate analysis. - ANSWER>>Data Wrangling Examples
Maintaining Databases examples/purpose - ANSWER>>Routines meant to help
performance, free up disk space, check for data errors, check for hardware faults,
update internal statistics, and many other obscure (but important) things.
Maintaining DB2® and Oracle databases involves updating statistics, monitoring
database, server, and space utilization, and planning backup and recovery
strategies. - an example of ? - ANSWER>>Maintaining databases
Project initiation falls under what role? - ANSWER>>Project Sponsor
How to find p-value? - ANSWER>>-look at alternative
-if less than, find area to the left of z value
-if greater than, find area to the right of z value
-if not equal to, if positive, find area to the right and double it. if negative, find
area to the left and double it.
creating tables and establishing relationships between those tables according to
rules designed both to protect the data and to make the database more flexible
by eliminating redundancy and inconsistent dependency. -
ANSWER>>normalization
OpenLayers - ANSWER>>
MATLAB - ANSWER>>The Matrix Laboratory language is used for a variety of
mathematical calculations and tasks
Ruby - ANSWER>>
Swift - ANSWER>>
