bubbles: 1 cm 45 Sec: bubbles 2 cm 45 Sec: no bubbles 60 Sec: bubbles: 1 ½ cm 60 Sec: bubbles 2 ¼ cm 60 Sec: no bubbles TRIAL 2: 0 Degrees Celsius: Room Temp.: 75 Degrees Celsius: 15 Sec: ½ cm bubbles 15 Sec: 1 cm bubbles 15 Sec: no bubbles/cloudy 30 Sec: 1 cm bubbles 30 Sec: 1 ½ cm bubbles 30 Sec: no bubbles/cloudy 45 Sec: 1 cm bubbles 45 Sec: 2 cm bubbles 45 Sec: no bubbles/cloudy 60 Sec: 1 ½ cm bubbles 60 Sec: 2 ¼ cm bubbles 60 Sec: no bubbles/cloudy Data Overview: Data was taken
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Labour (workers per week) | Output (toys per week) | 1 | 10 | 2 | 30 | 3 | 60 | 4 | 100 | 5 | 150 | 6 | 210 | 7 | 260 | 8 | 300 | 9 | 330 | 10 | 350 | (X-axis = labour , Y-axis =Output) (b) Average Product of Labour (APL) APL = Output/Labour Labour (workers per week) | Output (toys per week) | (Output / Labour)APL | 1 | 10 | 10 | 2 | 30 | 15 | 3 | 60 | 20 | 4 | 100 | 25 | 5 | 150 | 30 | 6 | 210 | 35 | 7 | 260 | 37.14
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SECTION 5 CHAPTER 4: ORGANIZATIONAL AND MANGERIAL ISSUES IN LOGISTICS 1. Discuss several issues that influence the organization of logistics activities within a firm. The organization of logistics activities within a firm depends on a number of factors, including the number and location of customers, as well as an organization’s size. The number and location of customers might influence whether a firm adopts a centralized or decentralized logistics organization. An organization’s
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sold per year @ $5 per unit = $4,000,000/360 Remember, since there are no balance sheets or operating statements, you will have to MANUALLY calculate the ACP. Just look at the numbers: 30% pay after 10 days + 50% pay after 30 days + 20% pay after 60 days. What’s the average? Voila! Also, for consistency, use 360 days = one year Answer: ADS= $11,111 ACP= 33 days 2. Given your answers to #1, what is the projected average receivables level on any given day? (HINT: Formula is ACP x ADS)
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language varies in each of her interviews; she adapts her speech for different audiences, such as children and adults. In her interview from, Blue Peter she is more animated and lively on the other hand in her interview from 60 Minutes she is very reminiscent and glum. In the 60 Minutes interview J K Rowling uses many fillers. Fillers occur particularly in the first section of the interview, as well as some false starts and stammers. “Erm so you have that but you â you forgot⦔. This suggests that
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100 | N/A | N/A | N/A | 5 | 10 | 100 | 50 | 150 | 10 | 5 | 15 | 3 | 20 | 100 | 80 | 180 | 5 | 4 | 9 | 2.3 | 30 | 100 | 103 | 203 | 3.33 | 3.43 | 6.76 | 1.7 | 40 | 100 | 120 | 220 | 2.5 | 3 | 5.5 | 3 | 50 | 100 | 150 | 250 | 2 | 3 | 5 | 5 | 60 | 100 | 200 | 300 | 1.67 | 3.33 | 5 | 15 | 70 | 100 | 350 | 450 | 1.43 | 5 | 6.43 | | TC = TFC + TVC TC0 = 100 + 0 = 100 TC10 = 100 + 50 = 150 TC20 = 100 + 80 = 180 TC30 = 100 + 103 = 203 TC40 = 100 + 120 = 220 TC50
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Section 7.1 92. Investing her bonus. Donna invested her $33,000 bonus and received a total of $970 in interest after one year. If part of the money returned 4% and the remainder 2.25%, then how much did she invest at each rate? x+y=33000 .04x+2.25y=970 x=-y+33000 .04-y+33000+2.25y=970 -4y+1320+.0225y=970 -.0175y=-1320+970 -.0175y-.0175=-350-.0175 y=20,000 x+20,000=33,000 x=33,000-20,000 x=13000 100. Ticket sales. Tickets for a concert were sold to adults for $3 and to students for $2
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then so does the other; and the triangle is isosceles and could have legs = 1, hypotenuse = [pic]. In a right triangle, if one of the acute angles is 30(, then the other is 60(; such a triangle could have a hypotenuse of 2 and legs of 1 and [pic]. Find the exact value of the six trigonometric functions of 45(, 30(, and 60(: | |Sine |Cosine |Tangent |Cotangent |Cosecant |Secant | |45(=(/4
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the film was in and how many weeks it was in the Top 60. By looking at this information and using descriptive statistics, we can come to some conclusions about this industry. Descriptive Statistics Variable | Sample Size | Mean | SE Mean | Standard Deviation | Range | Opening gross | 100 | 9.38 | 1.89 | 18.87 | 108.43 | Total gross | 100 | 33.04 | 6.32 | 63.16 | 380.15 | # of theaters | 100 | 1,278 | 138 | 1,379 | 3905 | Weeks in Top 60 | 100 | 8.680 | 0.0639 | 6.390 | 26.0 | Variable
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Acknowledgements The authors wish to thank the entire OII team for their support of OxIS research. Our particular thanks to Prof. Helen Margetts, Dr Rebecca Eynon and Martin Dimov for their contributions to this report. We also wish to acknowledge Kunika Kono and David Sutcliffe for their design and editorial support of this report. For their early contributions to OxIS we would like to thank Prof. Richard Rose, Dr Adrian Shepherd, and Dr Corinna di Gennaro. All have helped shape the evolution of
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