Apportionment Homework

Do My Homework!

Apportionment is a task that may never have everyone agree on the proper method of implementation. The idea is to fairly assign a specific number of seats to various states or regions based on population. Obviously states with larger populations should have more seats awarded, but the exact method of division is far from agreed upon. The purpose of this assignment is to study the basics of two well-known methods of apportionment and discuss their fairness.

The first method is the Hamilton method. For this fictitious situation there are ten states with a total population of 532188 among which 100 seats are to be awarded. The first step is to find the divisor:
D = 532188 / 100 = 5321.88.
The next step is to find the standard and lower quotas. This will be done for the first state with the understanding that the procedure is repeated for all remaining states. The standard quota is found by dividing the state’s population by the divisor:
Standard Quota (1) =  15475 / 5321.88 = 2.9078
Lower Quota (1) =      Integer (2.9079) = 2.
The last step before beginning apportionment is to also list the fractional part. This is merely what is left after subtracting the lower quota from the standard quota:
Fractional Part (1) =    2.9078 – 2 = 0.9078.

To begin, assign the lower quota to each state. The only exception is for a state whose lower quota is zero (like state 5 in this example). For this state assign one seat. In this example once this was done there were 96 seats assigned and 4 remaining. The distribution of assigned seats (in numerical order by state) is 2, 6, 18, 16, 1, 16, 8, 15, 10, and 4. In order to assign the remaining four seats the fractional parts are examined. Excluding state 5 (since it already has its upper quota of seats) examine the fractional parts and find the four largest. For this example those are states 1, 2, 8, and 10. Finally the four seats that remain to be awarded are assigned to the states with the larges fractional parts resulting in an apportionment of 3, 7, 18, 16, 1, 16, 8, 16, 10, and 5.

The average constituency for each state is found by dividing the population of the state by the number of seats awarded. In a perfect situation each state would have a constituency that is equal to the divisor. Obviously that is not the case, but states should have constituencies that are near the divisor. The constituency for state 1 is:
15475 / 3 = 5158.333.
The absolute unfairness of the apportionment is the difference between the largest constituency and the smallest constituency. The relative unfairness is ratio of the absolute unfairness to the smallest constituency. For this example these values are:
Absolute unfairness = 5521.625 – 369 = 5152.625
Relative unfairness = 5152.625 / 369 = 13.964.

The most obvious way that population change could affect this example is if 800 residents of state 2 either moved to or were reincorporated into state 4. This would reduce the population of state 2 to 34844 and increase the population of state 4 t o89146. The reason for picking these two states is that state 2 got the last additional seat due to the fractional parts and state 4 was next in line. The new fractional parts after this change would be
34844 / 5321.88 = 6.5473                   0.5473
89145 / 5321.88 = 16.7508                 0.7508.
This relatively small change in population would result in state 2 losing one of their seats and state 4 gaining that seat.

An Alabama paradox occurs when an increase in the total number of seats to be apportioned causes a state to lose one of its seats. The reason this happens is because states with larger populations have their fractional part increase at a greater rate. It is possible for enough states that are slightly lower than the victim state will have their fractional part surpass that of the victim state causing the loss of a seat. The Huntington-Hill method helps to avoid this paradox by assigning the additional seats using a geometric mean rather than a simple larger fractional part. Unfortunately it also has the possibility of violating the quota rule, where no state can be given less than its lower quota or more than its upper quota. As a possible check the apportionments were calculated (and results listed on the Excel sheet) for total seats of 101 through 106; no occurrence of the Alabama paradox was noted.

In the first application of the Huntington-Hill method the total number of seats awarded did not equal the number of seats available. Thus a new divisor needed to be attempted; an easy way to choose this was to divide the population by 99 instead of 100. This divisor produced a working solution, and is outlined here. The divisor and standard quotas were determined in the same manner as they were for the Hamilton method. After that the geometric mean of the upper quota and the lower quota for each state was found. For state 1 this resulted in:
Standard quota:          15475 / 5375.636 = 2.879
Geometric mean:         (2 * 3)1/2 = 2.449.
Since the fractional part of the standard quota is larger than the fractional part of the geometric mean, state 1 is assigned a number of seats equal to its upper quota (3). Compare this with the result for state 3:
Standard quota:          98756 / 5375.636 = 18.371
Geometric mea:           (18 * 19)1/2 = 18.493.
Here the fractional part of the standard quota is less than the fractional part of the geometric mean, so state 4 is assigned a number of seats equal to its lower quota (18). The final apportionment using this system is 3, 7, 18, 16, 1, 16, 8, 16, 10, and 5. Notice that this is the same apportionment achieved using the Hamilton method.

Since both apportionment methods result in the same division I feel that, at least in this case, apportionment is a fair way of dividing the seats. The only thing that possibly seems unfair is the constituency of state 5. The only way to rectify this that I see is to absorb state 5 into the other states leaving a total of 9 states. This is not a simple task, and would most certainly depend on which states bordered state 5. This was a very instructive project. It was complex enough to afford some rigor in determining the apportionments. It was also instructive in that it demonstrated both how apportionment methods can be fair and unfair.

Analyzing Counseling Theories







alden University


Analyzing Counseling Theories

Part 1: Chart

  Theory 1: Name Theory 2: Name
Background Theory



·      Use only bullet points; no sentences—delete this before beginning your one page chart. The boxes will expand to accommodate your points. ·
Human Nature



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Major Constructs



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  Chapter Author, Year Chapter Author, Year




Part 2: Reflection

  1. Describe a specific population of clients with whom you hope to work in the future. Explain why you have chosen this population and what you hope to accomplish with this client base. (Note this point will remain the same on future papers, if you want to keep it. Please delete.)
  2. Explain which one of the two theories in your chart would be the most effective in working with this client population and explain why.
  • Describe at least two interventions from your chosen theory you would suggest using and how these interventions would assist this client population in reaching counseling goals.






















Finn, A. (2011). Jungian analytical theory. In D. Capuzzi & D. Gross (Eds.). Counseling and psychotherapy: Theories and interventions. (5th ed., pp. 77- 94). Alexandria, VA: American Counseling Association.

Haley, M. (2011). Gestalt therapy. In D. Capuzzi & D. Gross (Eds.). Counseling and psychotherapy: Theories and interventions. (5th ed., pp. 167- 191). Alexandria, VA: American Counseling Association.

Johnson, A. (2011). Psychoanalytic theory.  Haley, M. (2011). Gestalt therapy. In D. Capuzzi & D. Gross (Eds.). Counseling and psychotherapy: Theories and interventions. (5th ed., pp. 97- 76). Alexandria, VA: American Counseling Association.


Note: Be sure to change your references to reflect those you have cited in the assignment.






Project Risk Management


Institutional Affiliation:











Both developing and developed world economies are facing more complex regulatory and compliance measures following the occurrence of several financial crisis, while capitalizing on opportunities in the growing world companies like MexiEnergy Inc. are required to understand new markets and navigate on any expected risks. Consequently, risk management remains at the top of any expansion corporate agenda. The most important way to manage any risk is to practice diversity. In essence, while MexiEnergy Inc. looks to add on its service provision it faces some risks, these are: an increase in complexity and uncertainty surrounding organizations as they search for innovative ways to expand into new markets and as it faces off against increasing competition and pushing the envelope on the usable technology.

As MexiEnergy expands, there will arise different problems of a more complex nature than experienced. These are like the mentioned political pressure caused to the “avoidable cost”. These costs which are termed to be low could be instigated in ways that hinder expansion of the companies’ energy resources. Apart from the pressure, there exists a risk to waste resources. The “take-or-pay” gas plan is projected to waste both time and resources in the expansion process. These challenges should be addressed as soon as they can be dealt with and should be included in MexiEnergy Inc risk management plan.






Quantified Risk Description Calculations
Exposure Factor (EF)

Examples are the above mentioned KNOWN risks.

This is the percentage of asset loss caused by the known and identified threats/risks. It is measured as percentage from 0 to 100% exposure factor.
Single Loss Expectancy(SLE)

This value could be used to identify the factor that is presented by the “take-or-pay” gas plan.

It is a product of asset value and the exposure factor. Asset Value multiplied by the exposure factor.


Annualized Rate of Occurrence(ARO)

The river as a source could quantized here.

It is the estimated frequency of a threat occurring with a year’s period. Calculated by diving the risk and the number of years. Example once in 10 years is 0.1.
Benefit Analysis It is the product of single loss expectancy and annualized rate of occurrence. Also known as the value of safeguard to a company. In the evaluation of benefit analysis there will be the use of Internal rate of return.

(Tan, 2002).

Qualitative Risk analysis is meant to put into tangible expressions any risk that may be perceived in the course of or even after project completion. The four mentioned qualitative analysis tools could be used by MexiEnergy Inc. to estimate the risks to be encountered in the project.


Apart from basic project planning, risk management involves specific planning for risk. In the planning for risks there are methods such as schedule modifications done to adjust the project by MexiEnergy. One of the schedule modifications to be done on the energy project would be to hold up on the purchasing power from independent producers. Scheduling this will enable rigorous investigations to the best companies to procure from. Since risk planning starts by exploring the initial project assumptions, another schedule modification for the product should be done to ensure that both of the goals Mr. Sam sets are met. The second modification ensures that natural gas is confirmed and that it is surplus enough to share among neighboring institutions.  This will ensure that the perceived goals are met with minimal risk.

Project charters, datasheets, or other documents used to initiate a project often include essential information on risk, as well as goals, staffing assumptions, and other information. Any risk information included in these early project descriptions is worth noting; sometimes projects believed to be risky are described as such, or there may be other evidence of project risk. Due to the importance of thoroughness in project management another recommended modification would be to ensure perfect work in any part of the project with stiff penalties. This modification will not encourage delays but will instead give ample time for employees on the contract to do perfect work—after all there is no room for failure. In addition, since the river is natural resource requiring approval, modifications are necessary in order to settle the whole issue.

Various schedule modifications ensure that the project runs more smoothly than it would have without the different modifications. Modifying project schedules efficiently, ensures that autonomous productivity is achieved in the project. That is, the modifications made ensure each department of the projects performs as expected.



Ding Tan. (2002). Quantitative Risk Analysis Step by Step. SANS Institute.

Ford’s decision to hire New Factory Workers in Canada















Ford’s decision to hire New Factory Workers in Canada

Ford has expanded the current workforce to 400 in Canada. This is in effort to supplement the 1000 employees that were hired last year at the Oakville plant in the construction of a new Edge crossover to go on sale in spring. The next generation Edge is expected to sell in over 100 countries that will include the Western Europe region for the first time. Further, the other reason for hiring is due to the low gas prices that have increased the demand for sports utility and pickup trucks. Despite the massive spending on expansion, there are cheaper labor rates. Amidst the competition by General Motors, Canada has become an automaker that consolidates the operations in Oshawa. Fiat-Chrysler is also responsible for spending $2 billion for a 14-week overhaul of the Windsor plant. Ford stated that earlier on in February, the company would hire another 1500 workers in the first quarter to meet demand for the pickup tracks. The current Ford case will be important as they will encourage new jobs and investments in the United States car markets.