Intro to Crime and Criminal Justice Third Essay Exam Write a ​minimum​ of 7 pages​ (Times New Roman, double space, 12pt font). As always, use information mainly from our text to answer the questions—but you must also supplement your answers with your own critical thinking and input as well. The following questions are designed to not be 'chapter specific'. Instead, they challenge you to use information from several chapters. Each answer should roughly be the same length​. ​Be sure to write and provide direct support for your answers from the text and/or other sources (e.g. in-text citations, page numbers, end of document references). 1. Do you think the criminal justice system “works” in the United States? Why or why not? Explain in detail and provide clear examples. Try to think about the big picture here, and include a discussion about system goals such as crime prevention or reduction, deterrence, rehabilitation cost/benefits, definitions of justice, etc. 2. This course introduced the notion that the criminal justice system and all its players are inherently and generally limited in terms of their ability to prevent or reduce crime. What is meant by this? Provide a robust explanation. Do you think that other institutions such as the family, schools, and organized religion are better at social control and preventing crime than the criminal justice system? If so, which ones and in what ways? This answer may partially depend upon how efficient you believe the criminal justice system is, and on your personal beliefs regarding the importance of family and other social institutions in regulating behavior—be sure to provide clear support for your answers. 3. Present and discuss some of the most common myths we have discussed in this course about the criminal justice system (e.g. the rationale behind pretrial preventive detention, minorities commit more crime, what the processing of cases looks like—plea bargaining and bail instead of trial, more officers and more technology will reduce crime, the crime rate is going up, criminals are dangerous and commit violent crime, etc.) MSL 5080, Methods of Analysis for Business Operations 1 Course Learning Outcomes for Unit VI Upon completion of this unit, students should be able to: 5. Explain the criteria for making decisions under organizational uncertainty. 6. Illustrate the various methods of decision-making under risk. Reading Assignment Chapter 3: Decision Analysis, pp. 67–85; and Section 3.10, Utility Theory, on pp. 88–89 Unit Lesson Types of Decision-Making Environments As you may recall from the previous unit, the Thompson Lumber example of proposed sales expansion (seen on pages 68–69 of the textbook) was explored with a condition of uncertainty. Thompson knew the payoffs/profits for each alternative under each of two outcomes (favorable market or unfavorable market), but he did not know the outcome of the mar ...

1. Intro to Crime and Criminal Justice
Third Essay Exam
Write a minimum of 7 pages (Times New Roman, double space,
12pt font). As always, use
information mainly from our text to answer the questions—but
you must also supplement your
answers with your own critical thinking and input as well. The
following questions are designed
to not be 'chapter specific'. Instead, they challenge you to use
information from several chapters.
Each answer should roughly be the same length. Be sure to
write and provide direct support
for your answers from the text and/or other sources (e.g. in-text
citations, page numbers,
end of document references).
1. Do you think the criminal justice system “works” in the
United States? Why or why not?
Explain in detail and provide clear examples.
Try to think about the big picture here, and include a discussion
about system goals such as
crime prevention or reduction, deterrence, rehabilitation
cost/benefits, definitions of justice, etc.
2. This course introduced the notion that the criminal justice
system and all its players are

2. inherently and generally limited in terms of their ability to
prevent or reduce crime. What is
meant by this? Provide a robust explanation.
Do you think that other institutions such as the family, schools,
and organized religion are
better at social control and preventing crime than the criminal
justice system? If so, which ones
and in what ways? This answer may partially depend upon how
efficient you believe the criminal
justice system is, and on your personal beliefs regarding the
importance of family and other
social institutions in regulating behavior—be sure to provide
clear support for your answers.
3. Present and discuss some of the most common myths we have
discussed in this course about
the criminal justice system (e.g. the rationale behind pretrial
preventive detention, minorities
commit more crime, what the processing of cases looks like—
plea bargaining and bail instead of
trial, more officers and more technology will reduce crime, the
crime rate is going up, criminals
are dangerous and commit violent crime, etc.)

3. MSL 5080, Methods of Analysis for Business Operations 1
Course Learning Outcomes for Unit VI
Upon completion of this unit, students should be able to:
5. Explain the criteria for making decisions under
organizational uncertainty.
6. Illustrate the various methods of decision-making under risk.
Reading Assignment
Chapter 3: Decision Analysis, pp. 67–85; and Section 3.10,
Utility Theory, on pp. 88–89
Unit Lesson
Types of Decision-Making Environments
As you may recall from the previous unit, the Thompson
Lumber example of proposed sales expansion (seen
on pages 68–69 of the textbook) was explored with a condition
of uncertainty. Thompson knew the
payoffs/profits for each alternative under each of two outcomes
(favorable market or unfavorable market), but
he did not know the outcome of the market for his decision.
This uncertainty was one of three classifications
of decision-making environments shown in Section 3.3 of the

4. textbook.
Decision-making under certainty has an attractive charm of
being simple in most ways: the decision maker
knows what is being offered in each of several choices, as in
choices of bonds yielding a certain interest rate
over a given time. Thompson was making a decision under
uncertainty—more than one outcome had to be
considered possible for each alternative, but he did not know
the probability of each outcome, and he has to
risk losing something held at value (his investment) to find out
the outcome (recall that in the case, “outcome”
was either a favorable or unfavorable market). For the third
decision-making environment, as gamblers and
card players know, there is decision-making under risk. Once
again, there are several outcomes possible for
each alternative. The probabilities of the outcomes are known
(six sides to a die, 52 cards in a normal deck,
13 cards of each suit in a normal deck), and the player has to
risk losing something held at value to find out
the outcome. This unit focuses, in turn, on tools you can use
when facing organizational uncertainty and risk.
Decision-Making Under Uncertainty
Analysts and scholars have established the following list of
decision-making criteria to choose from to best fit
the situation:
Optimistic: Of the alternatives in each outcome, the
best/maximum payoff for each is figured, and the
alternative with the maximum of these “maximums” is selected.
This can also be termed the maximax
method, which is indeed optimistic! This method of analysis can
work, but who has experienced a completely
optimistic situation? A leader has to be sure about the

5. calculations before using this method to choose, but it
is available. As indicated in the textbook, if the problem is
really one of minimizing the payoff the most, then
the minimums are figured, and the smallest minimum payoff is
selected.
Pessimistic: This criterion considers the lowest (minimum)
payoff for each alternative of each outcome, and
the alternative with the best (maximum) of the minimum
payoffs is the one to choose. It is like considering,
“this alternative will hurt the least,” and this method is also
termed the maximin way. Note that unlike what
many people believe, doing nothing is always an alternative,
which here may be a payoff of zero. Sometimes,
especially under uncertainty, it is apparently the best choice—at
least until leaders and their supporting
analysts know a bit more.
UNIT VI STUDY GUIDE
Decisions with Uncertainty and Risk
MSL 5080, Methods of Analysis for Business Operations 2
UNIT x STUDY GUIDE
Title
Criterion of Realism (Hurwicz Criterion): This is a method
philosophically between the optimistic and

6. pessimistic methods, as for this one, analysts obtain a
coefficient of realism (α), and then calculate a
weighted average to find the degree of optimism between 0 and
1. So when:
Weighted average = α (best payoff) + (1 – α) (worst payoff),
and α can be agreed on, then the expected payoff is “steered
toward realism” with this equation. As was the
case with the optimistic criterion, if the problem instead was
that of minimizing the payoff, then the best payoff
is the lowest of them, and the worst payoff would be the highest
of the choices.
Equally Likely (Laplace Criterion): This makes use of all the
alternative payoffs where before, only the
“best” and “worst” payoffs were considered, or there were no
more in the tables except high and low payoffs.
This approach regards all possible outcomes as equally likely,
and so that the average payoffs of the
alternatives are the ones to choose from. The best choice would
be either the highest value average payoff,
or the lowest if minimizing the payoff is the goal.
Minimax Regret: In this criterion, regret is synonymous with
opportunity cost (or loss). For any outcome, the
regret is the difference between the payoff realized after the
alternative was chosen for that outcome and the
payoff actually realized after a choice of alternative was made
for that outcome. As shown on page 71 and
Table 3.8 of the textbook, minimax regret is a useful method for
making reasonably sure that the regret will
not be more than a certain payoff amount for the alternative
selected.
Decision-Making Under Risk

7. As noted earlier, in decision analysis, uncertainty means the
probabilities are not known, and risk means the
probabilities are known, but in each classification, a decision
has to be made in conditions other than certain.
Under risk (the probabilities are known but the value to be
gained is unknown) until chosen, there have been
two approaches developed—where you can use calculations and
tables to figure an expected monetary value
(EMV) or an expected opportunity loss (EOL). These expected
values are really the mean values. You set
them as approximately the same thing, in the following
equation:
EMV(of the alternative) = ∑XiP(Xi)
This equation of the EMV determines it as the sum of each
alternative’s probability multiplied by the payoff for
a condition’s outcome, with all of these added together (∑) to
produce the EMV for the alternative. When this
sum is calculated, the analyst then proceeds to solve this
equation for the next alternative and all its
outcomes. For an EMV, when looking for the most value, the
alternative with the highest EMV is the best
choice; for minimizing the payoff, the lowest EMV is the best
choice.
A decision based on expected opportunity loss, or EOL, is very
close to minimizing an EMV payoff. The
equation is the same, with new terms:
EOL(of the alternative) = ∑XiP(Xi)
As shown on page 74 of the textbook, an alternative’s

8. probabilities and payoffs are multiplied for each
outcome, and then these terms are summed to determine that
alternative’s EOL; then usually the best
(lowest) EOL is chosen as the decision.
Decision Trees
A decision tree is a useful tool, not only in quantitative analysis
but in engineering as well, and in both fields
lead to a “good” decisions when all relevant factors are
considered. In this course and textbook, you explore
decision trees with nodes (locations where the tree will “branch
out” to another or more than one path) that
either show an outcome (e.g., favorable market or unfavorable
market) or two or more alternatives. These
analysis decision trees start at the left and flow toward the
right, as shown in the textbook’s Section 3.8
starting on page 79. Note that the nodes have been standardized
so that square-shaped nodes signify
decision points of two or more possible alternatives, and circle-
shaped nodes signify state-of-nature nodes
showing one or more possible outcome.
MSL 5080, Methods of Analysis for Business Operations 3
UNIT x STUDY GUIDE
Title
Decision trees have their own analysis steps, as shown on page

9. 80 of the textbook:
1. Define the problem. This is still critical here, or analysts will
be working with a faulty input.
2. Draw the decision tree. This step entails making sure the
right types of nodes are located in the right
positions, in the order that they occur from left to right. All
alternatives have to be determined and
represented in the tree.
3. Assign probabilities to the states of nature/outcomes. These
have to be known or researched.
4. Assign payoffs for each alternative and outcome.
5. Solve the problem by calculating the EMVs for each state of
nature/outcome. Because comparisons
of the end results are what decision-makers use to decide, these
calculations are started at the end,
on the far right of the tree (at the “branches’ ends) and calculate
back to the decision points. In the
example of the decision tree for Thompson Lumber as shown in
Figure 3.3 on pages 80–81, note that
the EMV calculations, calculating with payoffs and outcome
probabilities steers Thompson to the
prudent, but still positive, choice of building a small plant. The
calculations’ results based on the
probabilities skew the expectations away from both a bold but
risky choice of building a large plant
and also away from passing up the marketing opportunity.
You can refer to pages 81-85 to see how decision trees are a
better tool to use than tables when the
decisions get more complex—especially true with sequential

10. decisions. In analysis and engineering alike,
progress toward the final desired goal or decision may be held
up pending a preliminary decision or
performance of a prerequisite task. In the case of Thompson
Lumber as shown in Figure 3.4 on page 81, the
preliminary decision may be a market survey, which would
yield more precise state of nature/outcome
probabilities. The question is, should Thompson do the survey?
With the EMVs calculated, Thompson can
weigh the payoff benefit of the survey/no survey and the
expected payoffs calculated based on what the
surveys show. A smart business/government leader will know
that life contains few guarantees, but
leveraging mathematics to acquire a glimpse of what may
probably happen leads to good and better
decisions. A word of caution, shown in Section 3.10, Utility
Theory, pages 88–89: EMVs do not show
everything. The numbers of the EMVs may not make as much
sense as some practical reasoning to consider
the utility of the choices.
Reference
Render, B., Stair, R. M., Jr., Hanna, M. E., & Hale, T. S.
(2015). Quantitative analysis for management (12th
ed.). Upper Saddle River, NJ: Pearson.
Suggested Reading
The links below will direct you to a PowerPoint view of the
Chapter 3 Presentation. This will summarize and

11. reinforce the information from this chapter in your textbook.
Review slides 9–61 and 73–90 for this unit.
Click here to access a PowerPoint presentation for Chapter 3.
Click here to access the PDF view of the presentation.
For an overview of the chapter equations, read the “Key
Equations” on page 95 of the textbook.
Learning Activities (Nongraded)
Nongraded Learning Activities are provided to aid students in
their course of study. You do not have to submit
them. If you have questions, contact your instructor for further
guidance and information.
Work Solved Problems 3-1 to 3-3 on page 95–99 of the
textbook. Each problem is presented first, followed by
its solution. Challenge yourself to apply what you have learned,
and see if you can work out each problem
without first looking at the solution and only using the solution
to check your own work.
https://online.columbiasouthern.edu/bbcswebdav/xid-
78756143_1
https://online.columbiasouthern.edu/bbcswebdav/xid-
78756189_1
In an essay of no less than three pages, explain (1) the criteria
for decision-making under uncertainty and (2) decision-making
under risk. What is the difference between these two “other-
than-certainty” classifications? Include examples of each in the
essay.

12. Be sure to provide research to support your ideas. Use APA
style, and cite and reference your sources to avoid plagiarism.
Book:
Quantitative Analysis for Management (Barry Render)
Chapter 3: Decision Analysis, pp. 67-85; and Section 3.10,
Utility Theory, on pp. 88-89
Class MSL 5080 Methods for Analysis for Business Operations