Trend Detection and Forecasting
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| Owners: | Gabriela GarciaKateri Salk |
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| Created: | Jan 28, 2021 at 11:43 p.m. |
| Last updated: | Jan 29, 2021 at 9:59 p.m. |
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Abstract
Trend Detection and Forecasting
This lesson was adapted from educational material written by Dr. Kateri Salk for her Fall 2019 Hydrologic Data Analysis course at Duke University. This is the second part of a two-part exercise focusing on time series analysis.
Introduction
Time series are a special class of dataset, where a response variable is tracked over time. Time series analysis is a powerful technique that can be used to understand the various temporal patterns in our data by decomposing data into different cyclic trends. Time series analysis can also be used to predict how levels of a variable will change in the future, taking into account what has happened in the past.
Learning Objectives
1. Choose appropriate time series analyses for trend detection and forecasting
2. Discuss the influence of seasonality on time series analysis
3. Interpret and communicate results of time series analyses
Subject Keywords
Content
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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