PLEASEREBUTTALpROB.docxPLEASE REBUTTAL, RESPOND AND ANSWER EACH OF THE FOLLOWING QUESTIONS OR POST STATEMENTS. MUST BE 150 WORDS (PLEASE), WRITE IN 3RD PERSON. MUST BE 150 WORDS (PLEASE), WRITE IN 3RD PERSON.PLEASE MAKE SURE TO USE SCHOLARLY PEER REVIEWED ARTICLES AND PLACE EACH REFERENCE USED UNDER EACH ANSWER.
DQ 1
Probability theory is a central field of mathematics ,widely applicable to scientific,technological,and human situations involving uncertainty.the mostly common applications are situations such as games of chance,in which repeated trials of essentially the same procedure leads to deferring outcomes.whereas random guessing can be chosing without regard to any characteristics of individual members of the population or items, events,so that each has an equal chance of being selected.
In public management,(i.e in government entities ,agencies and departments).planning which is seen as more anticipative decision making process is every important activity of public managers.
This process allows the decision makers to determine a predicted arrangement of conditions,aims and measures of action in future with acknowledgment of features of system in relation to which the actions have been planned(Ackoff 1973).
In an attempt by government to estimate the following: life expectancy,fertility rate,the disease burden,the impact of a program, and population growth etc.for planning purposes the probability theory has been commonly used theory in public management.governments commonly use inferential statistics which is built on the foundation of probability theory(Dan osherson).the theory has been considered successful in guiding opinions about the conclusions to been drawn from data.
probability theory creates predictions that are fairly accurate,and representative,it involves degree of judgment, less time consuming.
References:
Lane,D.m.,Osherson ,D.(n.d).probability on line statistics Education: An interactive multi media course of study.rice university of Houston clear lake,and Tufts university.retrieved from from. http://on line stat book.com/2/probability/probability.html.
Pierre Simon de Laplace(1812) Analytical theory of probability
Akolmogorov(1933)Foundation of the theory of probability
DQ 2
Probability:
Probability is the logical assumption than a specific outcome (out of an assigned set of outcomes) will or will not occur. The assumption is both relative and subjective to the specific situation and number of possible outcomes (Lane & Osherson, 2013). Given this context, it can therefore be assumed that probabilities could be used in rational/synoptic decision-making models, given that those decision-making models list the (anticipated) possible outcomes (Chen, 2016).
Situation and Description:
I am a Lead Contracting Officer (Contract Administration for Acquisition) for the Special Teams in my Directorate. This is a new position that was purposed to have a person create extensive training resources specific to the duties of the Special Teams, including highly technical resources for requires collaboration inside and outside of the organization. When I began this job last year there were standards on how to create the training, so I had to design the standard.
In my decision-making for training, I weigh using a number of different training models that I am already familiar with:
Army-style: The Army training model consists of three phases (Crawl, Walk, Run) that outline the specific tasks required to complete an action. Training is provided for theory (Crawl), monitored hands-on (Walk), and unmonitored performance (Run). This method is great if the tasks for the actions do not require additional steps or choices (everything happens the same way every single time). This model is less great when each task varies greatly in the action to resolve it.
College-style: The College model is set up like a college course. There is a formal training plan (syllabus) that outlines the overall training in terms of goals (learning outcomes) and milestones (assignments). This method is great for new associates, or crossovers from other sections or disciplines. This model is less great under time constraints or with associates who have been doing the work and just need a refresher (i.e. due to policy changes).
DLA-style: The DLA style is a self-learning model. The Trainer creates desk guides outlining the step-by-step processes for each type of action, and includes helpful information (like regulatory citations, or tips to processing certain requests). This process is great for existing employees who just need an update, or for a situation that requires more action than process understanding (i.e. an elevated request that the Supervisor is working because of a Congressional Complaint).
The Probability Theory allows us to assume that for any given situation, that there is a probability of 0.33% that any choice in training models will be successful (approx.. 1:3). We can also look at the specifics of the situation and increase the probability of success by assigning a given number for using the most appropriate model (let’s say 0.4%), which falls in the Subjective Approach to Probability (since no two situations will ever be exactly alike) (Minutes, Leaf, & King, n.d.).
Situational Benefits to Probability Theory:
In using probability, we are forced to determine all possible outcomes. This allows the decision-maker(s) to think about issues with the choices and consider alternatives. It also allows for quantitative analysis of decisions over time, showing the probabilities and their results- which can give decision-makers an overview of how accurate their probability models are. This is very useful in my training situation, as it will allow me to determine if I need to revisit my methods to make any changes over specific periods (i.e. quarterly, semi-annually, annually, etc.). It will also provide me with reporting tools (metrics) to give Management and Senior Leadership an idea of how training is progressing.
References:
Chen, C. (2016). Advantages and disadvantages of rational decision-making model introduction. Retrieved fromhttp://www.academia.edu/8832272
Lane, D. M., & Osherson, D. (2013, August 4). Probability. Online Statistics Education: An Interactive Multimedia Course of Study [1.5]. Rice University, University of Houston Clear Lake, and Tufts University. Retrieved from http://onlinestatbook.com/2/probability/probability.html.
Minutes, A. O., Leaf, D., & King, S. (n.d.). Probability. OPRE 6301: Quantitative Introduction to Risk and Uncertainty in Business, University of Texas at Dallas. Retrieved from https://www.utdallas.edu/~scniu/OPRE-6301/documents/Probability.pdf
