C207 OA C207 Data-Driven Decision
Making OA 2026 – Latest Exam
Update, New Questions, Answers &
Study Guide
Descriptive Analytics - ANSWER-the use of data to understand past and current
business performance and make informed decisions
Predictive Analytics - ANSWER-the use of past data to model future outcomes
Prescriptive Analytics - ANSWER-use techniques that create models indicating the best
decision to make or course of action to take
4 components of Big Data - ANSWER-Structured and Unstructured data, large
quantities, cannot use traditional software and databases
Data Mining - ANSWER-finding hidden patterns within Big Data
3 Steps of Davenport-Kim Three-Stage Model - ANSWER-1. framing the problem
2. solving the problem
3. communicating results
Data Management - ANSWER-A process that focuses on data collection, storage, and
retrieval. Common data management functions include addition, deletion, modification,
and listing.
Continuous Data - ANSWER-Data that can be any value on a range
ex: age
Interval Data - ANSWER-Data that is within a range and an equal interval apart
ex: times, shoe sizes
Ratio Data - ANSWER-Data that have known intervals between values and a
meaningful zero value
,ex: income, inventory levels
Ratioooo = 0
Discrete Data - ANSWER-Numerical data that can be counted as whole numbers
ex: cars
Nominal Data - ANSWER-Data which consists of names, labels, or categories
ex: male/female
NOMinal = NAMes
Ordinal Data - ANSWER-Data that places objects into an order according to some
quality with higher order indicating more of that quality
ex: degrees
ORDinal = ORDered
Random Error - ANSWER-An error that will not repeat itself and occurs less in larger
samples of data
Systematic Error - ANSWER-An error that is consistently made throughout an
experiment, likely because of measurement or tool faultiness
Omission Error - ANSWER-An error because something (for example, data or survey
response) is missing.
Outlier - ANSWER-A value much greater or much less than the others in a data set
Measurement Bias - ANSWER-Bias from a poor representation of the population or a
sample that is not random
Response Bias - ANSWER-Tendency for subjects to respond with what they assume
the questioner wants to hear
Conscious Bias - ANSWER-Tendency for the surveyor to be seeking or leading to a
certain response
Skewness (Bias) - ANSWER-Measure of degree to which data "leans" toward one side
Observational Studies - ANSWER-Studies in which the researcher observes and
statistically analyzes when it is impractical to have control
Experimental Studies - ANSWER-Studies in which the independent variables are
directly manipulated and the effects on the dependent variable are examined
,Independent Variable - ANSWER-The experimental factor that is manipulated by
researcher, aka the predictor
Dependent Variable - ANSWER-The outcome factor; the variable that may change in
response to manipulations of the independent variable.
Blind Study - ANSWER-Participants are not told whether they're in the control or
experiment group
Double Blind Study - ANSWER-Participants and researchers are not told which group is
control or experiment
Triple Blind Study - ANSWER-Participants, experimenters, independent raters of
outcome, and data managers are unaware of who is control or experiment
Qualitative Data - ANSWER-Information describing color, odor, shape, or some other
physical characteristic
Quantitative Data - ANSWER-Data associated with mathematical models and statistical
numbers
Probability - ANSWER-The chance of an event occurring in the future
Independent Events - ANSWER-Events which the outcomes have no effect on each
others occurrence
Complementary Events - ANSWER-Only select possible outcomes
ex: coin flip landing heads/tails
Conditional Probability - ANSWER-the probability that one event happens given that
another event is already known to have happened
Intersection - ANSWER-Probability of an overlap of events
Intersection formula - ANSWER-P(AnB) = P(A) x P(B)
= prob. A x prob. B
Intersection keyword - ANSWER-AND
Union - ANSWER-Probability of multiple events occurring without overlap
Union formula - ANSWER-P(AuB) = P(A) + P(B) - P(AnB)
= prob. A + prob. B - overlap
Union keyword - ANSWER-OR
, Mutually Exclusive Events - ANSWER-Two events that cannot occur at the same time
Mutually Exclusive formula - ANSWER-P(AuB) = P(A) + P(B)
= prob. A + prob. B
Bayes Theorem - ANSWER-The probability of an event occurring based upon other
event probabilities.
Bays Theorem formula - ANSWER-P(A|B) = P(B|A) x P(A) all over P(B)
Mean - ANSWER-The arithmetic average of a distribution, obtained by adding the
scores and then dividing by the number of scores
Median - ANSWER-The middle score in a distribution; half the scores are above it and
half are below it
Mode - ANSWER-The most frequently occurring score(s) in a distribution
Variance - ANSWER-The square of the standard deviation
Standard Deviation - ANSWER-A measure of the distance of every score to the mean
Z-Score - ANSWER-Amount of standard deviations from data point to the mean
Normal Distribution - ANSWER-Mean = Median = Mode
Where all data points occur around the mean without bias to one side
Bell Curve - ANSWER-distribution of scores in which the bulk of the scores fall toward
the middle, with progressively fewer scores toward the "tails" or extremes
Bell Curve Levels - ANSWER-+/- 1 Sd = 34.1%
+/- 2 Sd = 13.6%
+/- 3 Sd = 2.1%
any other data = 0.2%
Range - ANSWER-Array of possibilities data may exist in
Percentiles - ANSWER-Value of which a percentage of the population falls in
Inter-quartile Range (IQR) - ANSWER-Difference between the first and third quartiles
Box Plot - ANSWER-Display of information based on a 5 number summary
Minimum (Box Plot) formula - ANSWER-Min. = Q1 - 1.5(IQR)
Making OA 2026 – Latest Exam
Update, New Questions, Answers &
Study Guide
Descriptive Analytics - ANSWER-the use of data to understand past and current
business performance and make informed decisions
Predictive Analytics - ANSWER-the use of past data to model future outcomes
Prescriptive Analytics - ANSWER-use techniques that create models indicating the best
decision to make or course of action to take
4 components of Big Data - ANSWER-Structured and Unstructured data, large
quantities, cannot use traditional software and databases
Data Mining - ANSWER-finding hidden patterns within Big Data
3 Steps of Davenport-Kim Three-Stage Model - ANSWER-1. framing the problem
2. solving the problem
3. communicating results
Data Management - ANSWER-A process that focuses on data collection, storage, and
retrieval. Common data management functions include addition, deletion, modification,
and listing.
Continuous Data - ANSWER-Data that can be any value on a range
ex: age
Interval Data - ANSWER-Data that is within a range and an equal interval apart
ex: times, shoe sizes
Ratio Data - ANSWER-Data that have known intervals between values and a
meaningful zero value
,ex: income, inventory levels
Ratioooo = 0
Discrete Data - ANSWER-Numerical data that can be counted as whole numbers
ex: cars
Nominal Data - ANSWER-Data which consists of names, labels, or categories
ex: male/female
NOMinal = NAMes
Ordinal Data - ANSWER-Data that places objects into an order according to some
quality with higher order indicating more of that quality
ex: degrees
ORDinal = ORDered
Random Error - ANSWER-An error that will not repeat itself and occurs less in larger
samples of data
Systematic Error - ANSWER-An error that is consistently made throughout an
experiment, likely because of measurement or tool faultiness
Omission Error - ANSWER-An error because something (for example, data or survey
response) is missing.
Outlier - ANSWER-A value much greater or much less than the others in a data set
Measurement Bias - ANSWER-Bias from a poor representation of the population or a
sample that is not random
Response Bias - ANSWER-Tendency for subjects to respond with what they assume
the questioner wants to hear
Conscious Bias - ANSWER-Tendency for the surveyor to be seeking or leading to a
certain response
Skewness (Bias) - ANSWER-Measure of degree to which data "leans" toward one side
Observational Studies - ANSWER-Studies in which the researcher observes and
statistically analyzes when it is impractical to have control
Experimental Studies - ANSWER-Studies in which the independent variables are
directly manipulated and the effects on the dependent variable are examined
,Independent Variable - ANSWER-The experimental factor that is manipulated by
researcher, aka the predictor
Dependent Variable - ANSWER-The outcome factor; the variable that may change in
response to manipulations of the independent variable.
Blind Study - ANSWER-Participants are not told whether they're in the control or
experiment group
Double Blind Study - ANSWER-Participants and researchers are not told which group is
control or experiment
Triple Blind Study - ANSWER-Participants, experimenters, independent raters of
outcome, and data managers are unaware of who is control or experiment
Qualitative Data - ANSWER-Information describing color, odor, shape, or some other
physical characteristic
Quantitative Data - ANSWER-Data associated with mathematical models and statistical
numbers
Probability - ANSWER-The chance of an event occurring in the future
Independent Events - ANSWER-Events which the outcomes have no effect on each
others occurrence
Complementary Events - ANSWER-Only select possible outcomes
ex: coin flip landing heads/tails
Conditional Probability - ANSWER-the probability that one event happens given that
another event is already known to have happened
Intersection - ANSWER-Probability of an overlap of events
Intersection formula - ANSWER-P(AnB) = P(A) x P(B)
= prob. A x prob. B
Intersection keyword - ANSWER-AND
Union - ANSWER-Probability of multiple events occurring without overlap
Union formula - ANSWER-P(AuB) = P(A) + P(B) - P(AnB)
= prob. A + prob. B - overlap
Union keyword - ANSWER-OR
, Mutually Exclusive Events - ANSWER-Two events that cannot occur at the same time
Mutually Exclusive formula - ANSWER-P(AuB) = P(A) + P(B)
= prob. A + prob. B
Bayes Theorem - ANSWER-The probability of an event occurring based upon other
event probabilities.
Bays Theorem formula - ANSWER-P(A|B) = P(B|A) x P(A) all over P(B)
Mean - ANSWER-The arithmetic average of a distribution, obtained by adding the
scores and then dividing by the number of scores
Median - ANSWER-The middle score in a distribution; half the scores are above it and
half are below it
Mode - ANSWER-The most frequently occurring score(s) in a distribution
Variance - ANSWER-The square of the standard deviation
Standard Deviation - ANSWER-A measure of the distance of every score to the mean
Z-Score - ANSWER-Amount of standard deviations from data point to the mean
Normal Distribution - ANSWER-Mean = Median = Mode
Where all data points occur around the mean without bias to one side
Bell Curve - ANSWER-distribution of scores in which the bulk of the scores fall toward
the middle, with progressively fewer scores toward the "tails" or extremes
Bell Curve Levels - ANSWER-+/- 1 Sd = 34.1%
+/- 2 Sd = 13.6%
+/- 3 Sd = 2.1%
any other data = 0.2%
Range - ANSWER-Array of possibilities data may exist in
Percentiles - ANSWER-Value of which a percentage of the population falls in
Inter-quartile Range (IQR) - ANSWER-Difference between the first and third quartiles
Box Plot - ANSWER-Display of information based on a 5 number summary
Minimum (Box Plot) formula - ANSWER-Min. = Q1 - 1.5(IQR)
