Time Series Analysis - 1 - Time Series in Excel - Time Series Forecasting - Data Science-Simplilearn
Introduction to Time Series Analysis and Forecasting
Skip to main content Skip to table of contents. Advertisement Hide. Introduction to Time Series and Forecasting. Front Matter Pages i-xiv. Pages
Skip to main content Skip to table of contents. Advertisement Hide. Introduction to Time Series and Forecasting. Authors view affiliations Peter J. Brockwell Richard A. Front Matter Pages i-xiv. Pages
A time series is a series of data points indexed or listed or graphed in time order. Most commonly, a time series is a sequence taken at successive equally spaced points in time. Thus it is a sequence of discrete-time data. Examples of time series are heights of ocean tides , counts of sunspots , and the daily closing value of the Dow Jones Industrial Average. Time series are very frequently plotted via line charts. Time series are used in statistics , signal processing , pattern recognition , econometrics , mathematical finance , weather forecasting , earthquake prediction , electroencephalography , control engineering , astronomy , communications engineering , and largely in any domain of applied science and engineering which involves temporal measurements. Time series analysis comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data.
You are currently using the site but have requested a page in the site. Would you like to change to the site? Douglas C. Montgomery , Cheryl L. Jennings , Murat Kulahci. Praise for the First Edition "…[t]he book is great for readers who need to apply the methods and models presented but have little background in mathematics and statistics.