A Term Paper On BUSINESS STATISTICS 1 Submitted To Dr. Md. Abul Kalam Azad Associate Professor Department of Marketing University of Dhaka Submitted By Group Name: “ORACLES” Section: B Department of Marketing (17th Batch) University of Dhaka Date of Submission: 12- 04-2012 Group profile “ORACLES” |
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University of Hull | Supply Chain Planning and Control-Individual assignment: Pony Group | | | | 4/13/2013 | 56130 Model leader: Riccardo Mogre | Student number: 201100320 Word count: 2,662 Contents 1. Introduction 2 2. Section 1: Demand forecast 2 2.1. Moving average 2 2.2. Simple Exponential Smoothing 3 2.3. Holt’s Model 4 2.4. Winter’s Model 5 2.5. Demand forecast for XYZ 8 3. Section 2: Aggregate planning 9 3.1. Aggregate planning Question
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deterministic quality because the initial conditions already lay out the future of the system and is defined by those initial conditions with no chance of randomness. Leonard points out three chaotic mathematical systems and they are; chaotic systems are non-linear, deterministic, and unstable in that they display
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Multicollinearity What multicollinearity is. Let H = the set of all the X (independent) variables. Let Gk = the set of all the X variables except Xk. The formula for standard errors is then sbk (1 R 2 s 1 RYH *y ) * ( N K 1) s X k 2 X k Gk 2 s 1 RYH *y Tolk * ( N K 1) s X k Vif k * 2 s 1 RYH *y ( N K 1) s X k Questions: What happens to the standard errors as R2YH increases? As N increases? As K increases? As the multiple correlation
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Focus on Application Systems of linear equations are categorized as algebraic equations to where each of the terms is a constant or is the product of the constant and variable. Linear equations regularly appear throughout a lifetime in common situations, because many of measurable quantities are considered proportional within other quantities and have a relation linearly. A simple way of understanding the linear system is to say that it is a collection of linear equations that involve a same set
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forecasting -Identify the components of a forecast -Be able to calculate the following forecast: -simple moving average forecast -weighted Moving Average Forecast -Understand the principles behind calculating: -exponential smoothing forecast -linear Trend forecast -Simple and Multiple regressions Note: for data forecasting you will use historical data to calculate future data Slide 3- The Role of Demand Forecasting -Designed to estimate future demand for planning -purchasing Decisions
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|[pic] |Course Syllabus | | |College of Natural Sciences | | |MTH/208 Version 6 | |
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Temperature°C | Humidity% | Rainmm | 100 | 28 | 85 | 10 | 110 | 28 | 88 | 5 | 110 | 28 | 90 | 5 | 120 | 31 | 85 | 8 | 125 | 31 | 88 | 5 | 135 | 31 | 90 | 0 | 135 | 34 | 88 | 3 | 145 | 34 | 90 | 0 | 160 | 34 | 92 | 0 | Result obtained from linear regression operation: Information obtained from the result is: Multiple regression equation: y = -280.135 + 5.272T + 20767H - 0.338R Standard error of estimate, se = 5.338 Correction coefficient, r =
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The Minoan civilization was a Bronze Age civilization that arose on the island of Crete and flourished from approximately the 27th century BC to the 15th century BC. It was rediscovered at the beginning of the 20th century through the work of the British archaeologist Sir Arthur Evans. Will Durant referred to it as "the first link in the European chain." The early inhabitants of Crete settled as early as 128,000 BC, during the Middle Paleolithic age. However it was not until 5000 BC that the first
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involving 25 data points, the standard error of estimate is calculated as S( = 2.0 and the Fts = 10, then the information from regression line (SSR) should be, a) 60 b) 50 c) 40 d) 30 e) None of the above 3. In a statistics course, a linear regression equation was computed to predict the final exam score from the first quiz score. The equation obtained was Y = 10 + 0.9 X, where Y is the final exam score and X is the first quiz score. A prediction interval for Al Bundy who scored 95
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