Statistical Standards Board has provided guidance on disclosures of transactions between related parties, for example, transactions between subsidiaries of a common parent. GAAP regarding related-party transactions requires all of the following disclosures except

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a. The nature of the relationship involved.?

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b. A description of the transactions for each period an income statement is presented.?

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c. The dollar amounts of transactions for each period an income statement is presented.?

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d. The effect on the cash flow statement for each period a cash flow statement is presented.?

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2. The Management's Discussion and Analysis (MD&A) section of an annual report?

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a. Includes the company president's letter.?

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b. Covers three financial aspects of a firm's business: liquidity, capital resources, and results of operations.?

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c. Is a technical analysis of past results and a defense of those results by management.?

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d. Covers marketing and product line issues.?

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3. Windham Company has current assets of $400,000 and current liabilities of $500,000. Windham Company's current ratio would be increased by?

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a. The purchase of $100,000 of inventory on account.?

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b. The payment of $100,000 of accounts payable.?

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c. The collection of $100,000 of accounts receivable.?

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d. Refinancing a $100,000 long-term loan with short-term debt?

1. Basic Methods (35 points) In Bayesian inference the beta distribution is often used as the prior distribution for observed data with a binomial distribution. The beta distribution is normalized using the beta function which is dened on the interval [0, 1]: B(,)=j{;lfn_1{1$)_ldi, as >0 Assuming or = 5, and fl = 3, solve the integral to ve decimal points using the following methods: (a) (By Hand) Exact analytical solution. (b) (By Hand) Basic (noncomposite) Trapezoidal rule. (c) (By Hand) Basic (noncomposite) Simpson's 1,13 rule. A Generative Adversarial Network (GAN) is a deep learning network that has the following theoretical basis. It makes use of forward and backward chaining, making it very similar to FOL inference. O It is unique from the other neural networks, as it uses a probablestic bayesian network, Of It uses game theory and is based on minimax, It uses constraint satisfaction and tries to satisfy all constraints in order to converge the network.Suppose a normal model N(u, o2) is assumed for these state average BMIs. Conduct Bayesian analysis for this data set to make inferences about the mean u and variance o' of the state average BMI. Suppose the noninformative prior p(/4, o") = = is assigned. (a)(10pts) Find the posterior distribution and the 95% HPD credible region for p. (b) (10pts) Find the posterior distribution and the 95% HPD credible region for a'.Purpose of the Prior Distribution 1 point possible (graded) The previous lecture gave an introduction to the Bayesian approach of statistical inference. One central component is the prior distribution. which in simple terms is a distribution by which the likelihood function is weighted by, in order to produce a posterior distribution. Which of the following statements about prior choice in the Bayesian framework is the most accurate? " The prior distribution is to be specified by the researcher in order to forecast the observation values in the experiment before observing them. "' The prior distribution is to be specified by the researcher in order to take into account previous knowledge about possible values of the parameter. "' The prior distribution is to be specified by the researcher in order to decide between different statistical models used for the likelihood function. I\"; You have used 0 of 2 attempts Factors in Determining the Prior 0 points possible {ungraded} When applying the Bayesian framework. we have considerable freedom in specifying the family of our prior distribution. Which of the following factors must we consider In deciding on our prior? [Choose all that apply.) ' Whether or not we could specify the parameters ofthe distribution so that its shape approximates our prior belief whether or not the support ofthe distribution is realistic based on our context ' How tractable it would be to compute the posterior distribution and perform inference from it, given the form of the likelihood function I\"; You have used 0 of 2 attempts