WGU C207 Data Driven Decision Making
Exam Prep Questions And Answers Graded A+
A city government is trying to determine the national origins of its recent
immigrant population. If a survey of the immigrant population is conducted in
English what type of error might be present in the data?
Omission Error
An Educator develops a new standardized test to measure math skills of ninth
graders. She has students in her home state of Ohio take the test. If the test is to
be used on a national level, what type of error might be found in her data?
Measurement Bias
Process of turning data or information into knowledge.
Analytics
3 Types of Analytics
descriptive, predictive, prescriptive
Descriptive Analytics
What has happened in the past?
Predictive Analytics
What will happen in the future based on what has happened in the past? Or looks at
one the impact of one variable on another.
Prescriptive Analytics
Decision models that indicate the best course of action
Types of Descriptive Analytics:
1.Graphical Analysis (Histogram, Run chart, scatter, Pareto)
2.Discovery of patterns (sums, averages, percentages)
Types of Predictive Analytics
1.Models (Time series/trend, regression, statistical quality control)
2.Simulation
Types of Prescriptive Analytics
1.Optimization Models
2.Simulation
3.Decision Analysis
Optimization Models
help make the best decision while subject to resource constraints (linear programming)
Simulation:
probability and statics to model uncertainty
Decision Analysis:
Develop on optimal strategy for making decisions (Decision tree)
Big Data:
structure or un structured data in large volumes that need manipulation to become
meaningful; Analysis of big data requires a system of organization
3 Stages of Davenport-Kim Model to Quantitative Decision Making:
,1. Frame the Problem
2. Solving the Problem
3. Communicating the results
Frame the problem includes...
1. Identify the problem
2. review what we already know
3. Chose the model and how to collect
Solving the Problem includes ...
collect the data and analysis the data
Communicating Results includes...
Communicate outcomes and act on results
4 Levels/ types of measurement
1. Nominal
2. Ordinal
3. Interval
4. Ratio
Nominal:
No intrinsic order; Ex. Male or Females Names, labels, categories that contain only two
either/or (ex. Color or eyes, Pass/fail)
Ordinal:
Has an intrinsic order; Ex. Levels of energy - low, med, high Categories according to
some quality, non-numeric (Satisfaction level, top 10)
Interval:
Can be added and subtracted but not multiplied or divided Has an order and all objects
have equal intervals; no natural zero point (you cannot compare) (Ex. Temperature,
Women's dress sizes)
Ratio:
Has a true zero and can be manipulated in any way Has a unique zero point and can be
compared (Ex. Age, income, prices)
Cleaning and organizing a data set that are collected; vital step and good
decisions rely on clean and valid data
Data Management
Data Management helps ensure that the data produced is the following 5 things:
1. Relevant
2. Complete
3. Accurate
4. Available
5. Timely
Error that is Unknown and unpredictable changed in environment; can be
minimized by large sample size
Random error
Error that is from instruments or experimental design; constantly occurs
Systematic Error
Error that occurs When action has not been taken or something is left out
Omission Error
, Error that includes Observation points that are distant from other observations;
can figure out if it is correct or incorrect
Outliers
A measure of the degree to which data leans towards one side
Bias / Skewedness
Bias that happens When the sample is not represented of the population
Measurement Bias
Bias that happens when the respondent or interviewer has agenda that is not the
whole truth
Information Bias
Bias that happens when Respondents say what they believe the interviewer
wants to hear
Response Bias
Bias that happens when a Surveyor is actively seeking a response
Conscious Bias
3 Types of Bias Mitigation:
1. Blind Study
2. Double Blind Study
3. Triple Blind Study
Triple Blind Study:
Data Analyzer, Data gatherer, and participant are not told
Double Blind Study:
Data gatherer and participant are not told
Blind Study:
Participant is not told
Qualitative Research:
Exploratory research, Data no Characterized by Number
Quantitative Research:
Quantifies the problem by assigning numerical value; ability to use measurements and
analytics
3 Elements to Experimental Study
Experimental Units
Treatments
Responses
The effect of said treatments on the units; Measure of performance
Responses
Procedure being applied to each study
Treatments
Objects being observed
Experimental Units
Responses: The effect of said treatments on the units; Measure of performance
A local school board is studying the impact of a proposed change in testing on
math scores. Bias can be introduced into the study by both students and
teachers. Which research technique would eliminate this type of bias?
Double blind study
What level of measurement are women's dress sizes (2,4,6, etc.)?
Exam Prep Questions And Answers Graded A+
A city government is trying to determine the national origins of its recent
immigrant population. If a survey of the immigrant population is conducted in
English what type of error might be present in the data?
Omission Error
An Educator develops a new standardized test to measure math skills of ninth
graders. She has students in her home state of Ohio take the test. If the test is to
be used on a national level, what type of error might be found in her data?
Measurement Bias
Process of turning data or information into knowledge.
Analytics
3 Types of Analytics
descriptive, predictive, prescriptive
Descriptive Analytics
What has happened in the past?
Predictive Analytics
What will happen in the future based on what has happened in the past? Or looks at
one the impact of one variable on another.
Prescriptive Analytics
Decision models that indicate the best course of action
Types of Descriptive Analytics:
1.Graphical Analysis (Histogram, Run chart, scatter, Pareto)
2.Discovery of patterns (sums, averages, percentages)
Types of Predictive Analytics
1.Models (Time series/trend, regression, statistical quality control)
2.Simulation
Types of Prescriptive Analytics
1.Optimization Models
2.Simulation
3.Decision Analysis
Optimization Models
help make the best decision while subject to resource constraints (linear programming)
Simulation:
probability and statics to model uncertainty
Decision Analysis:
Develop on optimal strategy for making decisions (Decision tree)
Big Data:
structure or un structured data in large volumes that need manipulation to become
meaningful; Analysis of big data requires a system of organization
3 Stages of Davenport-Kim Model to Quantitative Decision Making:
,1. Frame the Problem
2. Solving the Problem
3. Communicating the results
Frame the problem includes...
1. Identify the problem
2. review what we already know
3. Chose the model and how to collect
Solving the Problem includes ...
collect the data and analysis the data
Communicating Results includes...
Communicate outcomes and act on results
4 Levels/ types of measurement
1. Nominal
2. Ordinal
3. Interval
4. Ratio
Nominal:
No intrinsic order; Ex. Male or Females Names, labels, categories that contain only two
either/or (ex. Color or eyes, Pass/fail)
Ordinal:
Has an intrinsic order; Ex. Levels of energy - low, med, high Categories according to
some quality, non-numeric (Satisfaction level, top 10)
Interval:
Can be added and subtracted but not multiplied or divided Has an order and all objects
have equal intervals; no natural zero point (you cannot compare) (Ex. Temperature,
Women's dress sizes)
Ratio:
Has a true zero and can be manipulated in any way Has a unique zero point and can be
compared (Ex. Age, income, prices)
Cleaning and organizing a data set that are collected; vital step and good
decisions rely on clean and valid data
Data Management
Data Management helps ensure that the data produced is the following 5 things:
1. Relevant
2. Complete
3. Accurate
4. Available
5. Timely
Error that is Unknown and unpredictable changed in environment; can be
minimized by large sample size
Random error
Error that is from instruments or experimental design; constantly occurs
Systematic Error
Error that occurs When action has not been taken or something is left out
Omission Error
, Error that includes Observation points that are distant from other observations;
can figure out if it is correct or incorrect
Outliers
A measure of the degree to which data leans towards one side
Bias / Skewedness
Bias that happens When the sample is not represented of the population
Measurement Bias
Bias that happens when the respondent or interviewer has agenda that is not the
whole truth
Information Bias
Bias that happens when Respondents say what they believe the interviewer
wants to hear
Response Bias
Bias that happens when a Surveyor is actively seeking a response
Conscious Bias
3 Types of Bias Mitigation:
1. Blind Study
2. Double Blind Study
3. Triple Blind Study
Triple Blind Study:
Data Analyzer, Data gatherer, and participant are not told
Double Blind Study:
Data gatherer and participant are not told
Blind Study:
Participant is not told
Qualitative Research:
Exploratory research, Data no Characterized by Number
Quantitative Research:
Quantifies the problem by assigning numerical value; ability to use measurements and
analytics
3 Elements to Experimental Study
Experimental Units
Treatments
Responses
The effect of said treatments on the units; Measure of performance
Responses
Procedure being applied to each study
Treatments
Objects being observed
Experimental Units
Responses: The effect of said treatments on the units; Measure of performance
A local school board is studying the impact of a proposed change in testing on
math scores. Bias can be introduced into the study by both students and
teachers. Which research technique would eliminate this type of bias?
Double blind study
What level of measurement are women's dress sizes (2,4,6, etc.)?
