Teddy Bower is an outdoor clothing and accessories chain that purchases a line of parkas at $11 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 1,900 and a standard deviation of 1,300. Teddy Bower sells these parkas at $20 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). Use Table 13.4.

Note: Do not round intermediate calculations. If a part of the question specifies whether to use Table 13.4, or to use Excel, then credit for a correct answer will depend on using the specified method.

1. How many parkas should Teddy Bower buy from TeddySports to maximize expected profit? Use Table 13.4 and the round-up rule.

Note: Enter your answer as a whole number.

1. If Teddy Bower orders 3,250 parkas, what is expected leftover inventory? Use Table 13.4 and the round-up rule.

Note: Round your answer to 2 decimal places.

1. If Teddy Bower orders 3,250 parkas, what is expected sales? Use your result from Part b.

Note: Round your answer to 2 decimal places.

1. If Teddy Bower orders 3,250 parkas, what is expected profit? Use your results from Part band Part c.

Note: Round your answer to 2 decimal places.

1. How many parkas should Teddy Bower order to ensure a 98.5% in-stock probability? How many parkas should Teddy Bower's order? Use Table 13.4.

TABLE 13.4

The Distribution , F(Q), and Expected Inventory, I(Q), Functions for the Standard Normal Distribution

Function

z	F(z)	I(z)
-4.0	0.0000	0.0000
-3.9	0.0000	0.0000
-3.8	0.0001	0.0000
-3.7	0.0001	0.0000
-3.6	0.0002	0.0000
-3.5	0.0002	0.0001
-3.4	0.0003	0.0001
-3.3	0.0005	0.0001
-3.2	0.0007	0.0002
-3.1	0.0010	0.0003
-3.0	0.0013	0.0004
-2.9	0.0019	0.0005
-2.8	0.0026	0.0008
-2.7	0.0035	0.0011
-2.6	0.0047	0.0015
-2.5	0.0062	0.0020
-2.4	0.0082	0.0027
-2.3	0.0107	0.0037
-2.2	0.0139	0.0049
-2.1	0.0179	0.0065
-2.0	0.0228	0.0085
-1.9	0.0287	0.0111
-1.8	0.0359	0.0143
-1.7	0.0446	0.0183
-1.6	0.0548	0.0232
-1.5	0.0668	0.0293
-1.4	0.0808	0.0367
-1.3	0.0968	0.0455
-1.2	0.1151	0.0561
-l.1	0.1357	0.0686
-1.0	0.1587	0.0833
-0.9	0.1841	0.1004
-0.8	0.2119	0.1202
-0.7	0.2420	0.1429
-0.6	0.2743	0.1687
-0.5	0.3085	0.1978
-0.4	0.3446	0.2304
-0.3	0.3821	0.2668
-0.2	0.4207	0.3069
-0.1	0.4602	0.3509
0.0	0.5000	0.3989
0.1	0.5398	0.4509
0.2	0.5793	0.5069
0.3	0.6179	0.5668
0.4	0.6554	0.6304
0.5	0.6915	0.6978
0.6	0.7257	0.7687
0.7	0.7580	0.8429
0.8	0.7881	0.9202
0.9	0.8159	1.0004
1.0	0.8413	1.0833
1.1	0.8643	1.1686
1.2	0.8849	1.2561
1.3	0.9032	1.3455
1.4	0.9192	1.4367
1.5	0.9332	1.5293
1.6	0.9452	1.6232
1.7	0.9554	1.7183
1.8	0.9641	1.8143
1.9	0.9713	1.9111
2.0	0.9772	2.0085
2.1	0.9821	2.1065
2.2	0.9861	2.2049
2.3	0.9893	2.3037
2.4	0.9918	2.4027
2.5	0.9938	2.5020
2.6	0.9953	2.6015
2.7	0.9965	2.7011
2.8	0.9974	2.8008
2.9	0.9981	2.9005
3.0	0.9987	3.0004
3.1	0.9990	3.1003
3.2	0.9993	3.2002
3.3	0.9995	3.3001
3.4	0.9997	3.4001
3.5	0.9998	3.5001
3.6	0.9998	3.6000
3.7	0.9999	3.7000
3.8	0.9999	3.8000
3.9	1.0000	3.9000
4.0	1.0000	4.0000