Sanfase, a technology company in rockbourne, manufactures microprocessors for computers. its product is a lot more powerful than its competitors'. this scenario is an example of competitive inertia. true false

The blank is type of decision-maker who over analyzes information

Data pertaining to the current position of forte company are as follows: cash $437,500 marketable securities 170,000 accounts and notes receivable (net) 320,000 inventories 700,000 prepaid expenses 42,000 accounts payable 240,000 notes payable (short-term) 250,000 accrued expenses 310,000 required: 1. compute (a) the working capital, (b) the current ratio, and (c) the quick ratio. round ratios to one decimal place. 2. compute the working capital, the current ratio, and the quick ratio after each of the following transactions, and record the results in the appropriate columns of the table provided. consider each transaction separately and assume that only that transaction affects the data given. round to one decimal place. a. sold marketable securities at no gain or loss, 75,000. b. paid accounts payable, 135,000. c. purchased goods on account, 100,000. d. paid notes payable, 105,000. e. declared a cash dividend, 125,000. f. declared a common stock dividend on common stock, 45,000. g. borrowed cash from bank on a long-term note, 205,000. h. received cash on account, 130,000. i. issued additional shares of stock for cash, 635,000. j. paid cash for prepaid expenses, 15,000.

An important application of regression analysis in accounting is in the estimation of cost. by collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. consider the following sample of production volumes and total cost data for a manufacturing operation. production volume (units) total cost ($) 400 4000 450 5000 550 5400 600 5900 700 6400 750 7000 compute b 1 and b 0 (to 2 decimals if necessary). b 1 b 0 complete the estimated regression equation (to 2 decimals if necessary). = + x what is the variable cost per unit produced (to 1 decimal)? $ compute the coefficient of determination (to 4 decimals). note: report r 2 between 0 and 1. r 2 = what percentage of the variation in total cost can be explained by the production volume (to 2 decimals)? % the company's production schedule shows 500 units must be produced next month. what is the estimated total cost for this operation (to 2 decimals)? $