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.

Assume that a local bank sells two services, checking accounts and atm card services. the bank’s only two customers are mr. donethat and ms. beenthere. mr. donethat is willing to pay $8 a month for the bank to service his checking account and $2 a month for unlimited use of his atm card. ms. beenthere is willing to pay only $5 for a checking account, but is willing to pay $9 for unlimited use of her atm card. assume that the bank can provide each of these services at zero marginal cost.refer to scenario 17-5. if the bank is unable to use tying, what is the profit-maximizing price to charge for a checking account

Rate of return douglas keel, a financial analyst for orange industries, wishes to estimate the rate of return for two similar-risk investments, x and y. douglas's research indicates that the immediate past returns will serve as reasonable estimates of future returns. a year earlier, investment x had a market value of $27 comma 000; and investment y had a market value of $46 comma 000. during the year, investment x generated cash flow of $2 comma 025 and investment y generated cash flow of $ 6 comma 770. the current market values of investments x and y are $28 comma 582 and $46 comma 000, respectively. a. calculate the expected rate of return on investments x and y using the most recent year's data. b. assuming that the two investments are equally risky, which one should douglas recommend? why?

How do the percentages of the 65 customer satisfaction ratings in that actually fall into the intervals [formula62.mml ± s], [formula62.mml ± 2s], and [formula62.mml ± 3s] compare to those given by the empirical rule? do these comparisons indicate that the statistical inferences you made in parts b and c are reasonably valid? (round your answers to the nearest whole number. omit the "%" sign in your