Flag

Indicate whether each phrase is more descriptive of financial accounting or managerial accounting.

(a) May be subjective

Financial accounting

Managerial accounting

(b) Often used to obtain financing

Financial accounting

Managerial accounting

(c) Typically prepared quarterly or annually

Financial accounting

Managerial accounting

(d) May measure time or customer satisfaction

Financial accounting

Managerial accounting

(e) Future oriented

Financial accounting

Managerial accounting

(f) Has a greater emphasis on cost-benefit analysis

Financial accounting

Managerial accounting

(g) Keeps records of assets and liabilities

Financial accounting

Managerial accounting

(h) Highly aggregated statements

Financial accounting

Managerial accounting

(i) Must conform to external standards

Financial accounting

Managerial accounting

(j) Special-purpose reports

Financial accounting

Managerial accounting

(k) Decision-making tool

Financial accounting

Managerial accounting

(l) Income statement, balance sheet, and statement of cash flows

Financial accounting

Managerial accounting

Match the letter with its meaning. average of a value In a bivariate data set actual value in a bivariate data set p-hat population proportion Intercept of an LSRL P slope of an LSLR Y bar often used to represent a random variable y-hat sample proportion predicted value iria bivariate data setConsider a Markov chain {Xn, n = 0, 1, . ..} on the state space S = {0, 1, 2}. Suppose that the Markov chain has the transition matrix 2 10 10 10 2 P = 3 10 2 4 10 10 1. Show that the Markov chain has a unique stationary mass. 2. Let h denote the stationary mass of the Markov chain. Find h(x) for all x E S. 3. Show that the Markov chain has the steady state mass. 4. Let h* denote the steady state mass of the Markov chain. Find h*(x) for all x E S.1. Consider the Markov chain with state space {0, 1, 2} and transition matrix 1 2 P = HO 2 (a) Suppose Xo = 0. Find the probability that X2 = 2. (b) Find the stationary distribution of the Markov chain. (c) What proportion of time does the Markov Chain spend in state 2, in the long run? (d) Suppose X5 = 1. What is the expected additional number of steps (after time 5) until the first time the Markov chain will return to state 1