Introduction to Data Science Final Exam
"normalize" data - ANSWER-Process of structuring a relational database in accordance
with a series of normal forms in order to reduce data redundancy and improve data
integrity
Normalization makes sure that all of your data looks and reads the same way across all
records
Accuracy - ANSWER-Most intuitive performance measure and it is a ratio of correctly
predicted observations to the total observation
A great measure with symmetric datasets where values of false positive and false
negatives are almost the same
Algorithm - ANSWER-Set of instructions designed to perform a specific task
Created as functions
Finite sequence of well-defined, computer-implementable instructions, typically to solve
a class of problems or to perform a computation
All discrete probability distributions have - ANSWER-discrete random variable values
that can have zero probability
All sampling distributions require - ANSWER-random sampling
All statistics are - ANSWER-functions of sample data
Analytical Aspirations - ANSWER-Executives commit to analytics by aligning resources
and setting a timetable to build a broad analytical capability
Analytical company - ANSWER-Enterprise-wide analytics capability under development;
top executives view analytic capability as a corporate priority
Analyticall Impaired - ANSWER-Company has some data and management interest in
analytics
Analytically competitive organization - ANSWER-The company routinely reaps benefits
of its enterprise-wide analytics capability and confuses on continuous analytics review
ANOVA - ANSWER-Analysis of Variance Compares mean values of a contributes
variable for multiple categories/groups
Bag of words approach - ANSWER-A text is represented as the bag of its words
Way of extracting features from text for us in modeling
Simple and flexible
Vocab of known words and measure of the presence of known words
Has nothing to do with the order or structure of words
, Word count
Balanced scorecard approach - ANSWER-A top-down management system that
organizations can use to clarify their vision and strategy and transform them into action
Basic elements of a properly done survey sample - ANSWER-Randomly selected
elements from a list
A list of the units or elements of the population
A method to assure that key elements of the population are represented in the sample
Bayesian model - ANSWER-it is fundamentally all about modifying conditional
probabilities - it uses prior distributions for unknown quantities which it then updates to
posterior distributions using the laws of probability
Big data technologies - ANSWER-Utilized software that incorporates data mining, data
storage, data sharing, and data visualization, the comprehensive term embraces data,
data framework including tools and techniques used to investigate and transform data.
Binary file - ANSWER-A file containing data or instructions written in zeros and ones
(computer language).
Business rules helps set up the __ - ANSWER-Conceptual data model
Business understanding phase in CRISP-DM - ANSWER-the data scientists first starts
by identifying the business problem and business objectives
Categorical data - ANSWER-Data that consists of names, labels, or other nonnumerical
values
Characteristics of analytical leaders? - ANSWER-Passionate and driven and their
initiatives are aimed at substantial results
Classical confidence intervals - ANSWER-vary from one sample to the next
Classical model - ANSWER-uses techniques such as Ordinary Least Squares and
Maximum Likelihood - this is the conventional type of statistics that you see in most
textbooks covering estimation, regression, hypothesis testing, confidence intervals, etc.
Classification/Decision Tree - ANSWER-flowchart structure that includes chance event
outcomes
Each internal node represents a "test" on an attribute (e.g. whether a coin flip comes up
heads or tails), each branch represents the outcome of the test, and each leaf node
represents a class label (decision taken after computing all attributes). The paths from
root to leaf represent classification rules.
Example: Titanic success rate: can break down data to show the characteristics that
lead to survival or death
"normalize" data - ANSWER-Process of structuring a relational database in accordance
with a series of normal forms in order to reduce data redundancy and improve data
integrity
Normalization makes sure that all of your data looks and reads the same way across all
records
Accuracy - ANSWER-Most intuitive performance measure and it is a ratio of correctly
predicted observations to the total observation
A great measure with symmetric datasets where values of false positive and false
negatives are almost the same
Algorithm - ANSWER-Set of instructions designed to perform a specific task
Created as functions
Finite sequence of well-defined, computer-implementable instructions, typically to solve
a class of problems or to perform a computation
All discrete probability distributions have - ANSWER-discrete random variable values
that can have zero probability
All sampling distributions require - ANSWER-random sampling
All statistics are - ANSWER-functions of sample data
Analytical Aspirations - ANSWER-Executives commit to analytics by aligning resources
and setting a timetable to build a broad analytical capability
Analytical company - ANSWER-Enterprise-wide analytics capability under development;
top executives view analytic capability as a corporate priority
Analyticall Impaired - ANSWER-Company has some data and management interest in
analytics
Analytically competitive organization - ANSWER-The company routinely reaps benefits
of its enterprise-wide analytics capability and confuses on continuous analytics review
ANOVA - ANSWER-Analysis of Variance Compares mean values of a contributes
variable for multiple categories/groups
Bag of words approach - ANSWER-A text is represented as the bag of its words
Way of extracting features from text for us in modeling
Simple and flexible
Vocab of known words and measure of the presence of known words
Has nothing to do with the order or structure of words
, Word count
Balanced scorecard approach - ANSWER-A top-down management system that
organizations can use to clarify their vision and strategy and transform them into action
Basic elements of a properly done survey sample - ANSWER-Randomly selected
elements from a list
A list of the units or elements of the population
A method to assure that key elements of the population are represented in the sample
Bayesian model - ANSWER-it is fundamentally all about modifying conditional
probabilities - it uses prior distributions for unknown quantities which it then updates to
posterior distributions using the laws of probability
Big data technologies - ANSWER-Utilized software that incorporates data mining, data
storage, data sharing, and data visualization, the comprehensive term embraces data,
data framework including tools and techniques used to investigate and transform data.
Binary file - ANSWER-A file containing data or instructions written in zeros and ones
(computer language).
Business rules helps set up the __ - ANSWER-Conceptual data model
Business understanding phase in CRISP-DM - ANSWER-the data scientists first starts
by identifying the business problem and business objectives
Categorical data - ANSWER-Data that consists of names, labels, or other nonnumerical
values
Characteristics of analytical leaders? - ANSWER-Passionate and driven and their
initiatives are aimed at substantial results
Classical confidence intervals - ANSWER-vary from one sample to the next
Classical model - ANSWER-uses techniques such as Ordinary Least Squares and
Maximum Likelihood - this is the conventional type of statistics that you see in most
textbooks covering estimation, regression, hypothesis testing, confidence intervals, etc.
Classification/Decision Tree - ANSWER-flowchart structure that includes chance event
outcomes
Each internal node represents a "test" on an attribute (e.g. whether a coin flip comes up
heads or tails), each branch represents the outcome of the test, and each leaf node
represents a class label (decision taken after computing all attributes). The paths from
root to leaf represent classification rules.
Example: Titanic success rate: can break down data to show the characteristics that
lead to survival or death
