QMB 3200 MIDTERM UCF EXAM LATEST 2026 UPDATED QUESTIONS
AND VERIFIED 100% SOLUTIONS (2026/2027) |A+ GRADED
|GUARANTEED PASS
Data
the facts & figures collected, analyzed, and summarized for presentation and interpretation
Dataset
all the data collected for a particular analysis
Element
the entity on which data is collected
Variable
a characteristic of interest of an element
Observation
the variables associated with an individual element
Categorical
use numeric or ordinal values of measurement of categories
Quantitative
use numeric (quantitative) measures
The type of statistical analysis depends on whether
the variable is
categorical or quantitative
Cross-sectional
data collected at a similar point in time
Time Series
data collected over several time periods
Panel
combination of cross-sectional and time series data
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, Descriptive Statistics
describe data or variables
Population
is the set of all data/variables of a statistical analysis
Sample
is a subset of the population
Statistical Inference
uses data from a sample to make estimates and test hypothesis about the characteristics of a
population
Analytics
is the scientific process of transforming data for decision making
What are the three broad areas of data analytics?
Descriptive, predictive and prescriptive
Descriptive Analytics
which describe what has happened in the past
Predictive Analytics
uses statistical models from past data to predict the future [forecasting] or access the impact of
one variable on another [inference]
Prescriptive Analytics
uses models seeking to find a best (optimal) solution. Often these are some type of optimization
model
The difference between data and big data are
a. Volume - the number of observations.
b. Velocity - the speed at which data is collected.
c. Variety - the forms of data are of different types.
d. Veracity - the reliability of the data generated
Data mining
Focuses on extracting predictive information from big data
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AND VERIFIED 100% SOLUTIONS (2026/2027) |A+ GRADED
|GUARANTEED PASS
Data
the facts & figures collected, analyzed, and summarized for presentation and interpretation
Dataset
all the data collected for a particular analysis
Element
the entity on which data is collected
Variable
a characteristic of interest of an element
Observation
the variables associated with an individual element
Categorical
use numeric or ordinal values of measurement of categories
Quantitative
use numeric (quantitative) measures
The type of statistical analysis depends on whether
the variable is
categorical or quantitative
Cross-sectional
data collected at a similar point in time
Time Series
data collected over several time periods
Panel
combination of cross-sectional and time series data
1|Page
, Descriptive Statistics
describe data or variables
Population
is the set of all data/variables of a statistical analysis
Sample
is a subset of the population
Statistical Inference
uses data from a sample to make estimates and test hypothesis about the characteristics of a
population
Analytics
is the scientific process of transforming data for decision making
What are the three broad areas of data analytics?
Descriptive, predictive and prescriptive
Descriptive Analytics
which describe what has happened in the past
Predictive Analytics
uses statistical models from past data to predict the future [forecasting] or access the impact of
one variable on another [inference]
Prescriptive Analytics
uses models seeking to find a best (optimal) solution. Often these are some type of optimization
model
The difference between data and big data are
a. Volume - the number of observations.
b. Velocity - the speed at which data is collected.
c. Variety - the forms of data are of different types.
d. Veracity - the reliability of the data generated
Data mining
Focuses on extracting predictive information from big data
2|Page
