Question 1

Which of the following statements are false?

Accepted Answer

A)  The modeling process discussed in Data Analysis & Decision Making book is five-step process. 
B)  Dealing with uncertainty requires a basic understanding of probability. 
C)  Uncertainty is a key aspect of most business problems. 
D)  Data description and data inference are included under data analysis. 
A)  The modeling process discussed in Data Analysis & Decision Making book is five-step process. 
B)  Dealing with uncertainty requires a basic understanding of probability. 
C)  Uncertainty is a key aspect of most business problems. 
D)  Data description and data inference are included under data analysis.

Question 2

When we use simulation models to help make decisions,we do not deal with uncertainty at all,since we often must make inferences from the simulated data.

Accepted Answer

A) True 
 B)False

Question 3

Decision-making includes optimization techniques for problems with certainty,decision analysis for problems with certainty,and structured sensitivity analysis.

Accepted Answer

A) True 
 B)False

Question 4

Which of the following is not one of the important themes of your Data Analysis & Decision Making book?

Accepted Answer

A)  Data analysis 
B)  Dealing with uncertainty 
C)  Decision making 
D)  Data mining 
A)  Data analysis 
B)  Dealing with uncertainty 
C)  Decision making 
D)  Data mining

Question 5

Dealing with uncertainty includes measuring uncertainty and modeling uncertainty explicitly into the analysis.

Accepted Answer

A) True 
 B)False

Question 6

Data are usually meaningless until they are analyzed for trends,patterns,relationships,and other useful information.

Accepted Answer

A) True 
 B)False

Question 7

Graphical models can be very helpful for simple problems.For complex problems,however,graphical models usually fail to show the important elements of a problem and how they are related.

Accepted Answer

A) True 
 B)False

Question 8

Which of the following is an Excel add-in for simulation?

Accepted Answer

A)  PrecisionTree 
B)  TopRank 
C)  Solver 
D)  @Risk 
E)  StatTools 
A)  PrecisionTree 
B)  TopRank 
C)  Solver 
D)  @Risk 
E)  StatTools

Question 9

Data analysis includes data description,data inference,and the search for relationships in data.

Accepted Answer

A) True 
 B)False

Question 10

The modeling process discussed in Data Analysis & Decision Making book is a

Accepted Answer

A)  seven-step process 
B)  six-step process 
C)  five-step process 
D)  four-step process 
E)  three-step process 
A)  seven-step process 
B)  six-step process 
C)  five-step process 
D)  four-step process 
E)  three-step process

Which of the following statements are false?

When we use simulation models to help make decisions,we do not deal with uncertainty at all,since we often must make inferences from the simulated data.

Decision-making includes optimization techniques for problems with certainty,decision analysis for problems with certainty,and structured sensitivity analysis.

Which of the following is not one of the important themes of your Data Analysis & Decision Making book?

Dealing with uncertainty includes measuring uncertainty and modeling uncertainty explicitly into the analysis.

Data are usually meaningless until they are analyzed for trends,patterns,relationships,and other useful information.

Graphical models can be very helpful for simple problems.For complex problems,however,graphical models usually fail to show the important elements of a problem and how they are related.

Which of the following is an Excel add-in for simulation?

Data analysis includes data description,data inference,and the search for relationships in data.

The modeling process discussed in Data Analysis & Decision Making book is a

Describing the Distribution of a Single Variable

Finding Relationships Among Variables

Probability and Probability Distributions

Normal, Binomial, Poisson, and Exponential Distributions

Decision Making Under Uncertainty

Sampling and Sampling Distributions

Confidence Interval Estimation

Hypothesis Testing

Regression Analysis: Estimating Relationships

Regression Analysis: Statistical Inference

Time Series Analysis and Forecasting

Introduction to Optimization Modeling

Optimization Models

Introduction to Simulation Modeling

Simulation Models

Data Mining

Importing Data Into Excel

Analysis of Variance and Experimental Design

Statistical Process Control

Filters

Exam 1: Introduction to Data Analysis and Decision Making

Which of the following statements are false?

When we use simulation models to help make decisions,we do not deal with uncertainty at all,since we often must make inferences from the simulated data.

Decision-making includes optimization techniques for problems with certainty,decision analysis for problems with certainty,and structured sensitivity analysis.

Which of the following is not one of the important themes of your Data Analysis & Decision Making book?

Dealing with uncertainty includes measuring uncertainty and modeling uncertainty explicitly into the analysis.

Data are usually meaningless until they are analyzed for trends,patterns,relationships,and other useful information.

Graphical models can be very helpful for simple problems.For complex problems,however,graphical models usually fail to show the important elements of a problem and how they are related.

Which of the following is an Excel add-in for simulation?

Data analysis includes data description,data inference,and the search for relationships in data.

The modeling process discussed in Data Analysis & Decision Making book is a

Describing the Distribution of a Single Variable

Finding Relationships Among Variables

Probability and Probability Distributions

Normal, Binomial, Poisson, and Exponential Distributions

Decision Making Under Uncertainty

Sampling and Sampling Distributions

Confidence Interval Estimation

Hypothesis Testing

Regression Analysis: Estimating Relationships

Regression Analysis: Statistical Inference

Time Series Analysis and Forecasting

Introduction to Optimization Modeling

Optimization Models

Introduction to Simulation Modeling

Simulation Models

Data Mining

Importing Data Into Excel

Analysis of Variance and Experimental Design

Statistical Process Control

Filters