QUESTION 1 10 points Save Answer Teddy Bower is an outdoor clothing and accessories chain that purchases a line of parkas at $10 each from its Asian supplier, TeddySports. Unfortunately, at the time of the order placement, demand is still uncertain: Teddy Bower forecasts that its demand is normally distributed with a mean of 2100 and a standard deviation of 1200. Teddy Bower sells these parkas at $22 each. Unsold parkas have little salvage value; Teddy Bower simply gives them away to a charity (and also doesn't collect a tax benefit for the donation). Round your answer to 2 digits after the decimal point if it is not an integer. Do NOT use comma in your numeric answers. %, which is defined as a product that sells The probability that this parka turns out to be a "dog" is less than half of the forecast (use the standard normal table below). The underage cost is $ The overage cost is $ The critical ratio is parkas from Teddy Sports in order to maximize . Teddy Bower should buy its expected profit (use the standard normal table below). The maximum profit for the parka is $ If Teddy Bower orders 3000 parkas, the in-stock probability will be %, the expected leftover inventory will be parkas, the expected sales will be parkas, the expected and the mismatch cost will be $ (use the standard profit will be $ normal table below). TABLE 13.4 The Distribution, F(Q), and Expected Inventory, MQ), Functions for the Standard Normal Distribution Function Z F(z) Iz) z F(z) (2) Z F(z) I(z) -4.0 -1.3 .0968 1.4 .9192 .0000 .0000 .0000 .0000 .0455 .0561 1.4367 1.5293 -3.9 -1.2 . 1151 1.5 .9332 -3.8 .0001 .0000 -1.1 .1357 .0686 1.6 .9452 1.6232 -3.7 .0001 .0000 -1.0 . 1587 .0833 1.7 .9554 -3.6 .0002 .0000 -0.9 .1841 .1004 1.8 .9641 1.7183 1.8143 1.9111 -3.5 .0002 .0001 -0.8 .2119 .1202 1.9 .9713 -3.4 .0003 .0001 -0.7 2420 .1429 2.0 .9772 2.0085 -3.3 .0005 .0001 -0.6 2743 .1687 2.1 .9821 -3.2 .0007 .0002 -0.5 .3085 .1978 2.2 .9861 -3.1 .0003 -0.4 .3446 2304 2.3 .9893 .0010 .0013 -3.0 .0004 -0.3 3821 2668 2.4 .9918 2.1065 2.2049 2.3037 2.4027 2.5020 2.6015 2.7011 -2.9 .0019 .0005 -0.2 .4207 .3069 2.5 .9938 -2.8 .0026 -0.1 .4602 .3509 2.6 .9953 .0008 .0011 -2.7 .0035 .0 5000 .3989 2.7 .9965 -2.6 .0047 .00 15 .1 .5398 4509 2.8 .9974 2.8008 -2.5 .0062 .0020 .5793 .5069 2.9 .9981 2.9005 2 .3 -2.4 .0082 .0027 .6179 .5668 3.0 .9987 3.0004 -2.3 .0107 .0037 .4 .6554 .6304 3.1 .9990 3.1003 -2.2 .0049 .5 .6915 .6978 3.2 .9993 3.2002 .0139 .0179 -2.1 .0065 .6 .7257 .7687 3.3 .9995 3.3001 -2.0 .0228 .0085 .7 .7580 .8429 3.4 .9997 3.4001 -1.9 .0287 .0111 .8 .7881 3.5 .9998 3.5001 .9202 1.0004 -1.8 .0359 .0143 9 .8159 3.6 .9998 3.6000 -1.7 .0446 .0183 1.0 .8413 1.0833 3.7 .9999 -1.6 .0548 .0232 1.1 .8643 1.1686 3.8 .9999 3.7000 3.8000 3.9000 -1.5 .0668 .0293 1.2 .8849 1.2561 3.9 1.0000 -1.4 .0808 .0367 1.3 .9032 1.3455 4.0 1.0000 4.0000