...1 of 15 Assignm ent 2 Garment Industry Case Study MIS – Garment Industry Case Study 2 of 15 The Business Problem In common with the rest of the UK textile and garment industry, IGL faced problems of increasing competition from overseas suppliers, in particular relatively low-wage “Newly Industrialising Countries” like Hong Kong. In response to these competitive pressures, The Special Garment Group began searching for appropriate strategies to meet the challenge. In early 1983, they hired management consultants to study the future of their contract garments business. MIS – Garment Industry Case Study Organizational Structure CONGLOMERATE INTERNATIONAL GARMENTS LIMITED BOARD 3 of 15 PRODUCT GROUP 1 SPECIAL GARMENTS GROUP BOARD PRODUCT GROUP 3 CHIEF EXECUTIVE PROFIT CENTRE 1 PROFIT CENTRE n COMMERCIAL DIRECTOR FINANCE DIRECTOR DP MANAGER DP MANAGER MIS – Garment Industry Case Study 4 of 15 SADT Diagram Suppliers Retailers Business Objectives & Strategies Policies & Plans Investment Proposal Project Plan Concepts & Business Needs . Flexibility . Responsiveness Production Control MICS Development Project User Training Management Info Education & Training DP Staff (SDC & SGG) Hardware MICS Application Finance Technology MIS – Garment Industry Case Study 5 of 15 Investm ent Proposal 1. increase the proportion of high value-added merchandise 2. improve the speed of response...
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...Wiliam Gajski Ja idem na biologiju about an hour ago via mobile · Like Luka Lapanja iz cega ces ucit? jel imas nekakve knjige, skripte ili neki k pa da mogu fotokopirat about an hour ago via mobile · Like Wiliam Gajski Imam skripte kaj mi je dala od zene neka frendica kaj ide na pripreme iz bio.. briem da ima oko 130 str about an hour ago via mobile · Like · 1 Luka Lapanja Aj jel moš to donijet u školu, pa da si fotokopiram to 4 minutes ago · Like Wiliam Gajski moram pogledat dal mi opce doma il kod zene about a minute ago via mobile · Like Luka Lapanja dobro, samo molim te ako možeš to dofurat ovih dana a few seconds ago · Like Luka Lapanja pa ti ja slijedeći vratim a few seconds ago · Like Options OLDER POSTS Diana Dee Dee Jašarević jel ko napiso eng??? koja tema je najlaksa ( makar meni nijedna nije xd ) Like · · Follow Post · 5 hours ago Seen by 15 View all 9 comments Dominik Cvijanović Eee paa sad 4 hours ago · Like Diana Dee Dee Jašarević joj joj ... sto reci 4 hours ago · Like Options Antonija Gabrić jel gledala potacek izostanke? Like · · Follow Post · 8 hours ago Seen by 16 Luka Lapanja and Diana Dee Dee Jašarević like this. View all 15 comments Diana Dee Dee Jašarević kurvaa 7 hours ago via mobile · Like Antonija Gabrić 7 hours ago · Like Options Dominik Cvijanović Laura Šeremet nam je u vezi sa Biciklom tj sad je sa Motorkom hahahahahhahaha eee ako ona moze nac decka onda svatko moze hahahahaha ...
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...It’s not immediately obvious looking at these options which bank account Timmy should choose. At first glance, 8.4% compounded yearly seems to be the highest rate, but is it necessarily the best choice? Read on to learn about the mathematical theory to solve this problem, or skip down to see how you can quickly find the answer with your financial calculator. Effective Annual Rate (EAR): Mathematical Background The key to solving this problem is understanding the relationship between the interest rate and rate of compounding. While Timmy is quoted several different interest rates, the rate he will actually earn on his bank account in each case also depends on the number of times per year interest is compounded on each bank account. To answer this question we need to determine and compare the effective annual rate (the interest rate that Timmy actually earns) for each bank account option. Let’s start with a simple example: If you deposit $1000 in a bank account paying 10% interest annually, after one year you would have $1,100 in the bank account [$1000 x (1 + .1)1] assuming no additional deposits or withdrawals. If you deposit $1,000 in a bank account paying 10% interest compounded semiannually, this means you earn 5% every six months (two times per year) on your bank account. After one year, you would have a bank account balance of $1000 x (1 + .05)2 = $1,102.50. Notice that this is $2.50 higher than the bank account with 10% compounded once a year. The...
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...TI-84 Plus Step by Step Hypothesis Test for the Mean and the zDistribution (Data) 1. Enter the data values into L1. 1. Press STAT and move the cursor to TESTS. 1. Press l for ZTest. Page 438 1. Move the cursor to Data and press ENTER. 1. Type in the appropriate values. 1. Move the cursor to the appropriate alternative hypothesis and press ENTER. 1. Move the cursor to Calculate and press ENTER. Example TI8–1 This relates to Example 8–4 from the text. At the 10% significance level, test the claim that μ < 515, given the data values. 496 | 506 | 507 | 505 | 438 | 499 | 505 | 522 | 531 | 762 | 513 | 493 | 522 | 668 | 543 | 519 | 349 | 506 | 519 | 516 | 714 | 517 | 511 | 551 | 287 | 523 | 576 | 516 | 515 | 500 | 243 | 509 | 523 | 503 | 414 | 504 | The test statistic is z = −0.3583333333, and the P-value is 0.3600469966. Hypothesis Test for the Mean and the zDistribution (Statistics) 1. Press STAT and move the cursor to TESTS. 1. Press 1 for ZTest. 1. Move the cursor to Stats and press ENTER. 1. Type in the appropriate values. 1. Move the cursor to the appropriate alternative hypothesis and press ENTER. 1. Move the cursor to Calculate and press ENTER. Example TI8–2 At the 5% significance level, test the claim that μ > 42,000 given σ = 5230, , and n = 30. The test statistic is z = 1.319561037, and the P-value is 0.0934908728. TI-84 Plus Step by Step Hypothesis Test for the Mean and the t Distribution (Data) ...
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d# I$"# :1(,1%)# $"*:"8# 2$/>0# 0$"# >('# ,*(=%*# /+>(1)%0/(+# 2.20")# 8"2/,+# >1()# 0"'$+(*(,/'%*#/+>1%201(1)%0/(+#1()#2(>0-%1"#8"&"*(:)"+0#2(1"2%-#0$"#:(0"+0/%*#...
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...SN5410, SN54LS10, SN54S10, SN7410, SN74LS10, SN74S10 TRIPLE 3-INPUT POSITIVE-NAND GATES SDLS035A – DECEMBER 1983 – REVISED APRIL 2003 PRODUCTION DATA information is current as of publication date. Products conform to specifications per the terms of Texas Instruments standard warranty. Production processing does not necessarily include testing of all parameters. Copyright 2003, Texas Instruments Incorporated POST OFFICE BOX 655303 • DALLAS, TEXAS 75265 1 SN5410, SN54LS10, SN54S10, SN7410, SN74LS10, SN74S10 TRIPLE 3-INPUT POSITIVE-NAND GATES SDLS035A – DECEMBER 1983 – REVISED APRIL 2003 2 POST OFFICE BOX 655303 • DALLAS, TEXAS 75265 SN5410, SN7410, TRIPLE 3-INPUT POSITIVE-NAND GATES SDLS035 – DECEMBER 1983 – REVISED MARCH 1988 POST OFFICE BOX 655303 • DALLAS, TEXAS 75265 3 SN54LS10, SN74LS10, TRIPLE 3-INPUT POSITIVE-NAND GATES SDLS035 – DECEMBER 1983 – REVISED MARCH 1988 4 POST OFFICE BOX 655303 • DALLAS, TEXAS 75265 SN54S10, SN74S10, TRIPLE 3-INPUT POSITIVE-NAND GATES SDLS035 – DECEMBER 1983 – REVISED MARCH 1988 POST OFFICE BOX 655303 • DALLAS, TEXAS 75265 5 MECHANICAL DATA MCFP002A – JANUARY 1995 – REVISED FEBRUARY 2002 W (R-GDFP-F14) CERAMIC DUAL FLATPACK Base and Seating Plane 0.045 (1,14) 0.026 (0,66) 0.260 (6,60) 0.235 (5,97) 0.080 (2,03) 0.045 (1,14) 0.008 (0,20) 0.004 (0,10) 0.280 (7,11) MAX 1 14 0.019 (0,48) 0.015 (0,38) 0.050 (1,27) 0.390 (9,91) 0.335 (8,51) 0.005...
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...SN5410, SN54LS10, SN54S10, SN7410, SN74LS10, SN74S10 TRIPLE 3-INPUT POSITIVE-NAND GATES SDLS035A – DECEMBER 1983 – REVISED APRIL 2003 PRODUCTION DATA information is current as of publication date. Products conform to specifications per the terms of Texas Instruments standard warranty. Production processing does not necessarily include testing of all parameters. Copyright 2003, Texas Instruments Incorporated POST OFFICE BOX 655303 • DALLAS, TEXAS 75265 1 SN5410, SN54LS10, SN54S10, SN7410, SN74LS10, SN74S10 TRIPLE 3-INPUT POSITIVE-NAND GATES SDLS035A – DECEMBER 1983 – REVISED APRIL 2003 2 POST OFFICE BOX 655303 • DALLAS, TEXAS 75265 SN5410, SN7410, TRIPLE 3-INPUT POSITIVE-NAND GATES SDLS035 – DECEMBER 1983 – REVISED MARCH 1988 POST OFFICE BOX 655303 • DALLAS, TEXAS 75265 3 SN54LS10, SN74LS10, TRIPLE 3-INPUT POSITIVE-NAND GATES SDLS035 – DECEMBER 1983 – REVISED MARCH 1988 4 POST OFFICE BOX 655303 • DALLAS, TEXAS 75265 SN54S10, SN74S10, TRIPLE 3-INPUT POSITIVE-NAND GATES SDLS035 – DECEMBER 1983 – REVISED MARCH 1988 POST OFFICE BOX 655303 • DALLAS, TEXAS 75265 5 MECHANICAL DATA MCFP002A – JANUARY 1995 – REVISED FEBRUARY 2002 W (R-GDFP-F14) CERAMIC DUAL FLATPACK Base and Seating Plane 0.045 (1,14) 0.026 (0,66) 0.260 (6,60) 0.235 (5,97) 0.080 (2,03) 0.045 (1,14) 0.008 (0,20) 0.004 (0,10) 0.280 (7,11) MAX 1 14 0.019 (0,48) 0.015 (0,38) 0.050 (1,27) 0.390 (9,91) 0.335 (8,51) 0.005...
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d# I$"# :1(,1%)# $"*:"8# 2$/>0# 0$"# >('# ,*(=%*# /+>(1)%0/(+#...
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d# I$"# :1(,1%)# $"*:"8# 2$/>0# 0$"# >('# ,*(=%*# /+>(1)%0/(+#...
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...Chapter 3: Introduction to Reliability Theory Claver Diallo OUTLINE 1. Part 1: Basic Reliability Models 1. 2. 3. 1. 2. 3. 4. 5. System Reliability function Probability distributions Reliability Block Diagram Serial and Parallel Structures Stand-by Structure k-out-of n Structure Complex structure 2. Part 2: Reliability of Structures 3. Part 3: Reliability Allocation 4. References 2 2 2 2 2 2 2 2 Chapter 3 - Part 1: Basic Reliability Models SYSTEM System: a collection of components or items performing a specific function. 4 4 4 4 4 4 4 4 STATE OF A SYSTEM A system is considered to be in one of the two following states: In operation (Up) Failed (Down) Transition from one state to the other occurs according to a known or unknown probability function. de aF de aF delllliiiiaF de aF 5 5 5 5 5 5 5 5 noitca ecnanetniaM noitca ecnanetniaM noitca ecnanetniaM noitca ecnanetniaM riapeR riapeR riapeR riapeR e eruliaF gn arepO gn arepO gniiiittttarepO gn arepO SYSTEM LIFETIME Lifetime is a measure of performance. Lifetime is a measure of performance. In general, lifetime is measured by the number In general, lifetime is measured by the of hours the system was in operation. number of hours the system was in operation. It can also be measured by the number of It can also be measured by the number of km or miles raced, number of pages copied, pages copied, km or miles raced, number wheel rotations, …etc. of wheel rotations, …etc. Lifetime (T) is a...
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...RATES AND TABLES Marginal Tax Rates1 (MTR) |Taxable income (TI) |Tax on this TI (2012/13) | |$0 - $18,200 |Nil | |$18,201 - $37,000 |19 cents for each $1 over $18,200 | |$37,001 - $80,000 |$3,572 plus 32.5 cents for each $1 over $37,000 | |$80,001 - $180,000 |$17,547 plus 37 cents for each $1 over $80,000 | |$180,001 and over |$54,547 plus 45 cents for each $1 over $180,000 | 1. Australian residents, whole year. Low Income Tax Offset (LITO) |Taxable income (TI) |Reduction in offset (RI) |Maximum offset | |$0 - $37,000 |Nil |$445 | |$37,001 - $66,666 |(TI - $37,000) x 0.015 |$445 - RI | |$66,667 and above |$445 |Nil ...
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...ingeniero diseña una herramienta para trabajar en máquinas las cuales se encuentran a distintas temperaturas. El único parámetro de diseño que él puede seleccionar en este punto es el material con que se recubrirá la herramienta y cuenta con cuatro alternativas. El ingeniero no tiene control sobre los extremos de temperatura que tendrán las máquinas donde operarán las herramientas y sabe por experiencia que es probable que la temperatura influya en la duración de de la herramienta. El ingeniero probará la herramienta a tres temperaturas: 100 ºF, 200 ºF y 300 ºF. Se prueban dos herramientas a cada combinación de material de recubrimiento y temperatura y las 24 pruebas se ejecutan al azar. Tipo de material Temperatura (ºF) 100 200 300 Ti 1 4 2 10 12 15 15 58 2 5 3 5 7 5 7 32 3 4 4 10 11 4 6 39 4 3 3 12 12 10 12 52 Tj 28 79 74 181 Solución.- i) Ho: σj² = σ² Vj Ho: σj² ≠ σ² al menos uno Vj Aplicando la dócima Cochran: Cc = 2 / 14.5 = 0.14 < > Ct,n-1,r-,95% = 0.60 Entonces: Cc < Ct Ho ii) Ho: Bj = 0 Vj Ho: Bj ≠ 0 al menos uno Vj SCT = (N-1) x S² SCT = (24 – 1) x 16.78 SCT = 385.96 SCTr = 36 / 2 + 64 / 2 + 64 / 2 + 36 / 2 +484 / 2 + 144 / 2 + 441 / 2 + 576 / 2 + 900 / 2 + 144 / 2 +100 / 2 + 484 / 2 - 181² / 24 SCTr = 1686.5 – 1365.04 SCTr = 321.4 SCE = SCT - SCTr SCE = 64.56 ANVA: F.V. G.L. S.C. S.C.M. Fc Tratamiento 12 – 1 = 11 321.4 29.22 5.43 Error...
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...You can use StatCrunch to assist with the calculations. A link for StatCrunch can be found under Tools for Success in Course Home. Here is also a link: http://statcrunch.pearsoncmg.com/statcrunch/larson_les4e/dataset/index.html. You can also find additional help on both confidence intervals and StatCrunch in the Online Math Workshop under Tab: “MAT300 Archived Workshops”. Specifically you will be looking for Hypothesis Tests and Using Technology – Hypothesis Testing. Submit your answers in Excel, Word or pdf format. Submit your file through the M&M® project link in the weekly course content. Be sure to state clear hypotheses, test statistic values, critical value or p-value, decision (reject/fail to reject), and conclusion in English (what does reject/fail to reject the null mean in terms of your hypotheses). When doing calculations for the color proportions, keep at least 4-6 decimal places sample proportions, otherwise you will encounter large rounding errors. Masterfoods USA states that their color blends were selected by conducting consumer preference tests, which indicated the assortment of colors that pleased the greatest number of people and created the most attractive overall effect. On average, they claim the following percentages of colors for M&Ms® milk chocolate candies: 24% blue, 20% orange, 16% green, 14% yellow, 13% red and 13% brown. 3 pts. Test their claim that the true proportion of blue M&Ms® candies is 0.24 at the 0.05 significance level...
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...205 TR 1:30 – 2:45 p.m., EV 207 Text and Required Supplies A Graphical Approach to College Algebra, 6th Edition by John Hornsby, Margaret Lial, Gary Rockswold ©2014 Prentice Hall. Description | | ISBN-10 | ISBN-13 | Approximate Cost | MyMathLab access code | Required | 032119991X | 9780321199911 | $75–100 | Hardcopy or Kindle | Optional | 0321920309 | 9780321920300 | $145–196 | Hardcopy bundled with MML | Optional | 978-0321909817 | 032190981X | $200–290 | The MyMathLab code can be purchased from the Arkadelphia bookstores or online. MWF MyMathLab CourseID: carpenter58666 TR MyMathLab CourseID: carpenter61414 A graphing calculator is required. Any TI newer than a TI-83 is highly recommended, for example, the TI-83+, TI-84+, or TI-nspire. The mathematics department strongly recommends the TI-Nspire CAS if you will take Calculus 1 or above. Course Prerequisite(s) A score of 20 on the ACT Mathematics Section, or equivalent score, or a grade of “C” or better in Intermediate Algebra from an accredited institution is required. However, it is recommended that your ACT score be at least 22. If you are using Intermediate Algebra as a prerequisite and took it at another school, then be prepared to show your transcript to your instructor, or you may be dropped from College Algebra. If you have less than 20 ACT score, then you may take a departmental exam that costs approximately $15 to be allowed into College Algebra. Your instructor will provide instructions if you...
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...MAT 300 M&Ms® Project Part 4 (21 pts) Use the M&Ms® data to complete this assignment. You will be using the methods of 7.4 for the color proportions and 7.2 for the mean number of candies per bag. For the Bonus you will be using the methods of 7.5. You can use StatCrunch to assist with the calculations. A link for StatCrunch can be found under Tools for Success in Course Home. Here is also a link: http://statcrunch.pearsoncmg.com/statcrunch/larson_les4e/dataset/index.html. You can also find additional help on both confidence intervals and StatCrunch in the Online Math Workshop under Tab: “MAT300 Archived Workshops”. Specifically you will be looking for Hypothesis Tests and Using Technology – Hypothesis Testing. Submit your answers in Excel, Word or pdf format. Submit your file through the M&M® project link in the weekly course content. Be sure to state clear hypotheses, test statistic values, critical value or p-value, decision (reject/fail to reject), and conclusion in English (what does reject/fail to reject the null mean in terms of your hypotheses). When doing calculations for the color proportions, keep at least 4-6 decimal places sample proportions, otherwise you will encounter large rounding errors. Masterfoods USA states that their color blends were selected by conducting consumer preference tests, which indicated the assortment of colors that pleased the greatest number of people and created the most attractive overall effect. On average, they...
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