Please help me with this, havent taken accounting in awhile.Recrea.pdf

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Please help me with this, havent taken accounting in awhile. Recreate the journal entry that Sensor made when it sold the stock to Greenco. How much gain was recognized on the sale of the stock? How much cash inflow did this transaction create for Sensor? Solution.

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Please help me and explain 1. If all other agents choose a level of activity e, the payoff of agent i can be expressed as V(ei, e). In this case the optimization problem becomes max ei V(ei, e), Using the optimization problem, show the the conditions for coordination failures. And also discuss coordination failures with help of the game theoretical structures such as the battle of the sexes, prisoners\' dilemma and the stag hunt bu giving the real cases in the economy. Solution Problem of coordination in a shared production process. Let ej be the effort (input) of player i in the production of a public good, c. The production function is c = f(ei,e) with fi > 0 and f2> 0. Agents have identical utility functions defined over consumption and effort U(c,e), with U1 > 0, U2 < 0, and U() quasi-concave. These preferences, together with the production function, generate agent i\'s payoff function: (1) V(ei,e) = U(f(ej,e),ej. Note that V12= U1f2> 0, so the model exhibits positive spillovers. Differentiating the payoff function with respect to ei and e yields (2) V12 = U1f12 + U1lflf2 + U12f2. that preferences between consumption and effort are separable. A necessary condition for strategic complementarity is then that inputs be complementary within the production process (/12 > 0). Increases in e will induce increases in ej if /12 is large enough to offset the reduction in the marginal utility of consumption brought about by f2 > 0. If U() is linear, /12 > 0 is sufficient for strategic complementarities. Note further that - V12 UJ1/2 + Ullfl2 V1l -[U11 (fl)2 + U1f/1 + U22] The necessary condition for multiplicity (p > 1) is (4) U1(/12 + /11) + U1l[(/l)2 + /1/2] _ -U22. Multiple Equilbria are thus more likely when the utility function is not very concave with respect to consumption and effort; when inputs are highly complementary in production; and when the production function is not very concave with respect to own effort..

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please help and be as detail as you can 1. Variation is a key statistic used in the most analytical studies. what are the implications of the high level of variations vs. low level of variation in a sample data 2. what are the implications Solution 1. In statistics, analysis of variance (ANOVA) is a collection of statistical models, and their associated procedures, in which the observed variance in a particular variable is partitioned into components attributable to different sources of variation. In its simplest form, ANOVA provides a statistical test of whether or not the means of several groups are all equal, and therefore generalizes t-test to more than two groups. Doing multiple two-sample t-tests would result in an increased chance of committing a type I error. For this reason, ANOVAs are useful in comparing two, three, or more means. 2. the act of implicating or the state of being implicated.

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Please help Lot, Xn and Yn have the distributions shown above. Find the expected value and variance of Xn and Yn. What does the Chebyshev inequality\'- tell us about the convergence of Xn and Yn? Is Yn convergent in probability? If so, to what value? Solution 1. E(X) = 0*1/n + 1*1/n = 1/n ; V(X) = E(X^2) - (E(X))^2 = (0*1/n + 1*1/n) - (1/n)^2 = 1/n - 1/n^2 = (n-1)/(n^2) E(Y) = 0*1/n + n*1/n = 1 ; V(Y) = E(Y^2) - (E(Y))^2 = (0*1/n + n^2/n) - (1) = n-1 2.Pr(|X-1/n|>k*sqrt(V(X))) <= 1/(k^2) for k>=1 Pr(|Y-1|>k*sqrt(V(Y))) <= 1/(k^2) for k>=1 3. No its not convergent as Sum of P(X) not converging to 1.

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In BC’s nearly-decade-old “new” curriculum, the curricular competencies describe the processes that students are expected to develop in areas of learning such as mathematics. They reflect the “Do” in the “Know-Do-Understand” model. Under the “Communicating” header falls the curricular competency “Explain and justify mathematical ideas and decisions.” Note that it contains two processes: “Explain mathematical ideas” and “Justify mathematical decisions.” I have broken it down into its separate parts in order to understand--or reveal--its meaning. The first part is commonplace in classrooms. By now, BC math teachers—and students—understand that “Explain mathematical ideas” means more than “Show your work.” Teachers consistently ask “What did you do?” and “How do you know?” This process is about retelling, not just of steps but of thinking. The second part happens less frequently. Think back to the last time that you observed a student make—a necessary precursor to justify—a mathematical decision. “Justify” is about defending. Like “explain,” it involves reasoning; unlike “explain,” it also involves opinion and debate. In order to reinterpret the curricular competency “Explain and justify mathematical ideas and decisions,” I will continue to take apart its constituent part “Justify mathematical decisions” and carefully examine the term “mathematical decisions.” What, exactly, is a “mathematical decision”? Below, I will categorize answers to this question. These categories, and the provided examples, may help to suggest new opportunities for students to justify.

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