DATA ANALYTICS FIRST EXAM
QUESTIONS WITH COMPLETE
SOLUTIONS
1. What is Statistics? What are the two main categories of statistics? - Answer-
•Statistics - collection of mathematical techniques to characterize and interpret data
•Two main categories of Statistics:
1.Descriptive Statistics - describe a sample of data
2.Inferential Statistics - draw inferences or conclusions regarding a population of
data, by analyzing a sample of data
List and define the most common Descriptive Statistics. - Answer-•Mean (a.k.a.
Average) - sum of all of the values in an observation divided by the number of
observations in a sample
•Median - the middle value in a sorted order of observations in a sample
•Mode - most frequently occurring value in a sample of observations
1. What is Dispersion and what is the difference among Range, Variance, and
Standard Deviation? - Answer-•Dispersion - mathematical methods used to estimate
or describe the degree of variability among the values in a sample of observations
•Measures of Dispersion
•Range - difference between the largest and smallest value in a given data set
•Variance - measure of deviation of all values in a data set from the Mean of the data
set (σ2)
•Standard Deviation - square root of the Variance; also measures deviation of a data
set values around a Mean (σ)
What is a Normal Distribution? What is the difference between Skewness and
Kurtosis? - Answer-•Normal Distribution - data values that are perfectly symmetrical
on both sides of a Mean, creating a Normal or "Bell" Curve
•Any data set can be "Normalized" (or Standardized) to fit a Normal Curve by
computing the z (or Standard) score (z = x - μ / σ)
•Skewness - measure of the degree to which a data set is offset (i.e., skewed) from
the Mean of the data set
•Kurtosis - height of the peak of the curve in a Normal Curve
1. What is Regression and how does it differ from Correlation? - Answer-•Regression
- statistical technique used to model the dependence of one variable (Dependent or
Output) on one or more other variables (Independent or Input). Linear Regression
allows prediction of Dependent Variable (y), based on changing values of the
Independent Variable (x).
•Correlation - measures the level of association between two variables, but does not
assume that one variable's value is dependent on another (i.e., there is no
Dependent nor Independent Variables present). Therefore, Correlation cannot be
used for Prediction.
, 1. What is Time Series Forecasting? Give examples. - Answer-•Time Series - the
use of mathematical modeling to predict future values, based on previously observed
valuesExamples: Sales over time, stock performance over time, temperature over
time, etc.
1. What is a Report? What are the most common types of reports? - Answer-•Report
- any communication artifact prepared with the specific intent of conveying
information in a digestible form to whomever needs it, whenever, and wherever they
need it
•Most common types of reports:
•Metric Management - convey state of KPIs (Key Performance Indicators)
•Dashboard-Type - provide a range of KPIs on one screen
•Balanced Scorecard-Type - provide KPIs within the context of agreed-upon
thresholds of performance (e.g., Green, Yellow, Red "traffic lights")
1. Who is credited with inventing the modern chart? What information did it show? -
Answer-•William Playfair in 1786
•Showed debts owed to, and by, England from 1700 - 1780
1. Explain the difference between Data Visualization and Visual Analytics? - Answer-
data visualizations: •Aimed at "What happened?," or "What is happening?"
visual analytics: •Aimed at "Why is it happening?," and "What is more likely to
happen next?"
1. What is a Dashboard? What are the most common dashboard characteristics? -
Answer-•Dashboards provide a visual display of important information that is
consolidated and arranged on a single screen, so that information can be digested at
a single glance, and easily "drilled into" for more detail
•Dashboard Characteristics:
•Use visual components
•Navigation is transparent to the user
•Combine data from a variety of systems into a single view
•Allow drill-down and drill-through to underlying detail
•Present information in "real-time," or near real-time
•Require little or no custom coding to implement, deploy, and maintain
1. Distinguish among Descriptive, Predictive, and Prescriptive Analytics. What are
examples of each? - Answer-•Descriptive Analytics - What is happening now? What
has happened?
•Reporting, Dashboards, Scorecards, & Data Warehousing
•Predictive Analytics - What will happen? Why will it happen?
•Data Mining, Text Mining, Web/Media Mining, & Forecasting
•Prescriptive Analytics - What should I do? Why should I do it?
•Optimization, Simulation, Decision Modeling, & Expert Systems
1. According to William Inmon, what are the characteristics of a Data Warehouse
(DW)? - Answer-•Data Warehouse - subject-oriented, integrated, time-variant,
nonvolatile collection of data that support managerial decision making
•Once again, the "Walmart of an Organization's Data"
QUESTIONS WITH COMPLETE
SOLUTIONS
1. What is Statistics? What are the two main categories of statistics? - Answer-
•Statistics - collection of mathematical techniques to characterize and interpret data
•Two main categories of Statistics:
1.Descriptive Statistics - describe a sample of data
2.Inferential Statistics - draw inferences or conclusions regarding a population of
data, by analyzing a sample of data
List and define the most common Descriptive Statistics. - Answer-•Mean (a.k.a.
Average) - sum of all of the values in an observation divided by the number of
observations in a sample
•Median - the middle value in a sorted order of observations in a sample
•Mode - most frequently occurring value in a sample of observations
1. What is Dispersion and what is the difference among Range, Variance, and
Standard Deviation? - Answer-•Dispersion - mathematical methods used to estimate
or describe the degree of variability among the values in a sample of observations
•Measures of Dispersion
•Range - difference between the largest and smallest value in a given data set
•Variance - measure of deviation of all values in a data set from the Mean of the data
set (σ2)
•Standard Deviation - square root of the Variance; also measures deviation of a data
set values around a Mean (σ)
What is a Normal Distribution? What is the difference between Skewness and
Kurtosis? - Answer-•Normal Distribution - data values that are perfectly symmetrical
on both sides of a Mean, creating a Normal or "Bell" Curve
•Any data set can be "Normalized" (or Standardized) to fit a Normal Curve by
computing the z (or Standard) score (z = x - μ / σ)
•Skewness - measure of the degree to which a data set is offset (i.e., skewed) from
the Mean of the data set
•Kurtosis - height of the peak of the curve in a Normal Curve
1. What is Regression and how does it differ from Correlation? - Answer-•Regression
- statistical technique used to model the dependence of one variable (Dependent or
Output) on one or more other variables (Independent or Input). Linear Regression
allows prediction of Dependent Variable (y), based on changing values of the
Independent Variable (x).
•Correlation - measures the level of association between two variables, but does not
assume that one variable's value is dependent on another (i.e., there is no
Dependent nor Independent Variables present). Therefore, Correlation cannot be
used for Prediction.
, 1. What is Time Series Forecasting? Give examples. - Answer-•Time Series - the
use of mathematical modeling to predict future values, based on previously observed
valuesExamples: Sales over time, stock performance over time, temperature over
time, etc.
1. What is a Report? What are the most common types of reports? - Answer-•Report
- any communication artifact prepared with the specific intent of conveying
information in a digestible form to whomever needs it, whenever, and wherever they
need it
•Most common types of reports:
•Metric Management - convey state of KPIs (Key Performance Indicators)
•Dashboard-Type - provide a range of KPIs on one screen
•Balanced Scorecard-Type - provide KPIs within the context of agreed-upon
thresholds of performance (e.g., Green, Yellow, Red "traffic lights")
1. Who is credited with inventing the modern chart? What information did it show? -
Answer-•William Playfair in 1786
•Showed debts owed to, and by, England from 1700 - 1780
1. Explain the difference between Data Visualization and Visual Analytics? - Answer-
data visualizations: •Aimed at "What happened?," or "What is happening?"
visual analytics: •Aimed at "Why is it happening?," and "What is more likely to
happen next?"
1. What is a Dashboard? What are the most common dashboard characteristics? -
Answer-•Dashboards provide a visual display of important information that is
consolidated and arranged on a single screen, so that information can be digested at
a single glance, and easily "drilled into" for more detail
•Dashboard Characteristics:
•Use visual components
•Navigation is transparent to the user
•Combine data from a variety of systems into a single view
•Allow drill-down and drill-through to underlying detail
•Present information in "real-time," or near real-time
•Require little or no custom coding to implement, deploy, and maintain
1. Distinguish among Descriptive, Predictive, and Prescriptive Analytics. What are
examples of each? - Answer-•Descriptive Analytics - What is happening now? What
has happened?
•Reporting, Dashboards, Scorecards, & Data Warehousing
•Predictive Analytics - What will happen? Why will it happen?
•Data Mining, Text Mining, Web/Media Mining, & Forecasting
•Prescriptive Analytics - What should I do? Why should I do it?
•Optimization, Simulation, Decision Modeling, & Expert Systems
1. According to William Inmon, what are the characteristics of a Data Warehouse
(DW)? - Answer-•Data Warehouse - subject-oriented, integrated, time-variant,
nonvolatile collection of data that support managerial decision making
•Once again, the "Walmart of an Organization's Data"
