Data Visualization and Communication Project Topic – Visualization “ Over 100 Years of U.S. Oil Production ” BRIEF DESCRIPTION OF THE PROJECT: The data set provides information on the annual production of crude oil in the United States from 1900 to 2020. It includes data on the total amount of crude oil produced in barrels per day, as well as information on the top-producing states and fields. This data set can be used to analyze trends in U.S. oil production over time and to understand the historical context of the country's oil industry. It is often used by researchers, policymakers, and industry professionals in the energy sector. OBJECTIVES: 1) Development of models and forecasts of future U.S. oil production based on historical data, to inform decision-making related to energy policy, investment, and business strategy. 2) Provide an accurate and comprehensive source of information on U.S. crude oil production over a long period of time, ...
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Visualization “Over 100 Years of U.S. Oil Production”
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BRIEF DESCRIPTION OF THE PROJECT: The data set provides information on the annual production of crude oil in the United States from 1900 to 2020. It includes data on the total amount of crude oil produced in barrels per day, as well as information on the top-producing states and fields. This data set can be used to analyze trends in U.S. oil production over time and to understand the historical context of the country's oil industry. It is often used by researchers, policymakers, and industry professionals in the energy sector. OBJECTIVES: 1) Development of models and forecasts of future U.S. oil production based on historical data, to inform decision-making related to energy policy, investment, and business strategy. 2) Provide an accurate and comprehensive source of information on U.S. crude oil production over a long period, which can be used to identify trends and patterns, as well as potential drivers of produ...
Modelling and forecasting using exponential smoothing technique
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Introduction: The main objective of this project was to implement the various forecasting techniques on the data set provided to us. The forecasting techniques used in the project are ARIMA models, simple exponential smoothing, holt’s method, and holt’s winters. The data provided to me was on the import and export of oil and non-oil products for a period of 26 years, this data was in a monthly format. Loading the required data loading data from the clipboard Investment income <- read.delim('clipboard', header = FALSE) Investment Income Qtr1 Qtr2 Qtr3 Qtr4 2000 264 146 262 76 2001 164 222 39 173 2002 232 49 168 225 2003 46 183 247 51 2004 193 234 23 191 2005 255 54 150 223 2006 52 188 252 53 2007 195 230 ...