The word zero came via French zéro from Venetian zero‚ which (together with cypher) came via Italian zefiro from Arabic صفر‚ ṣafira = "it was empty"‚ ṣifr = "zero"‚ "nothing". This was a translation of the Sanskrit word shoonya (śūnya)‚ meaning "empty". The first known English use was in 1598.[4][5][6][7] ------------------------------------------------- History Mesopotamia By the middle of the 2nd millennium BC‚ the Babylonian mathematics had a sophisticated sexagesimal positional numeral system
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WEATHER ANALYSIS & FORECASTING ** Weather Analysis: process of collecting‚ compiling‚ analyzing and transmitting the observational data of atmospheric conditions *this data & analysis is then used to forecast future weather conditions * Types of data: * Each weather station‚ 10‚000 around the world‚ collects the same data at the same time‚ at least 4 times per day(0000‚ 0600‚1200‚ 1800 GMT) * Most US stations also collect data continuously or at least every hour
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Zagreb‚ Croatia Electricity price forecasting – ARIMA model approach Tina Jakaša #1‚ Ivan Andročec #2‚ Petar Sprčić *3 Hrvatska elektroprivreda Ulica grada Vukovara 37‚ Zagreb‚ Croatia 2 # tina.jakasa@hep.hr ivan.androcec@hep.hr 1 * HEP Trade Ulica grada Vukovara 37‚ Zagreb‚ Croatia 2 petar.sprcic@hep.hr Abstract— Electricity price forecasting is becoming more important in everyday business of power utilities. Good forecasting models can increase effectiveness of producers
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Forecasting model for dry bulk sea freight Facilitating Lantmännen to make better procurement decisions Frans Kaltea Joel Odland Division of Engineering Logistics Faculty of Engineering Box 118 SE 221 00 Lund‚ Sweden This article is a summary of a master thesis written at the Division of Engineering
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Manager’s Guide to Forecasting by David M. Georgoff and Robert G. Murdick Harvard Business Review Reprint 86104 J A N U A RY– F E B R U A RY 1 9 8 6 HBR Manager’s Guide to Forecasting David M. Georgoff and Robert G. Murdick E arly in 1984‚ the Houston-based COMPAQ Computer Corporation‚ manufacturer of IBMcompatible microcomputers‚ faced a decision that would profoundly affect its future. Recognizing that IBM would soon introduce its version of the portable computer and threaten
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Qualitative Forecasting Approaches Qualitative forecasting methods are based primarily on human judgement. Quantitative forecasting methods are based primarily on the mathematical modelling of historical data. Here we provide a brief overview of the most important qualitative forecasting approaches. In many environments the time horizon is closely linked to the type of forecasting method used. Longer term and higher level forecasting will often require qualitative forecasting techniques. Such techniques
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relation exists when averages are related. ■ A deterministic relation is true by definition. ■ Specifying the Regression Model ■ Dependent variable Y is caused by X. ■ X variables are independently determined from Y. ■ Least Squares Method ■ Minimize sum of squared residuals. [pic] [pic] Measuring Regression Model Significance ■ Standard Error of the Estimate SEE) increases with scatter about the regression line. [pic] Goodness of Fit
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its importance‚ forecasting the exchange rate level has been a challenge for academics and market practitioners since the collapse of the Bretton Woods system. Empirical results from many of the exchange rate forecasting models in the literature have not yielded satisfactory results. This paper is constructed for the purpose of comparing the forecast performance of various competing models that have been suggested to forecast exchange rates. An overview and classifications of models are summarized
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Melany Fava Section 1: Descriptive Research Study Design 1a. What topic are you proposing to describe? Dieting in Weymouth High School students. 2a. Which approach to psychology would be most interested in describing this topic? Social 3a. Which of the three descriptive research methods will you use? Survey 4a. Thoroughly describe how you will design this research study with specific attention to sampling‚ wording-effect and various biases when applicable. I will create a 10-question
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Manufacturing and Distribution against Seasonal Sales Demand PEPSICO BUSINESS NEEDS AND CHALLENGES PepsiCo approached PCA‚ seeking improvements to how they managed their supply-chain planning and forecasting operations — their ability to optimize manufacturing‚ distribution and warehousing of hundreds of different beverage products and snack foods against seasonal sales projections across European‚ Middle East and Asian continents. Under-production meant lost revenue; over-production resulted in unnecessary
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