Time series cross-correlations and the NOAA Global Climate at a Glance (1910-2015) : global ocean and land temperatures /
This dataset example introduces researchers to estimating cross-correlations between two time series variables. A cross-correlation examines the correlation between two time series variables contemporaneously and at various lagged values. Cross-correlations help researchers understand if two variabl...
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| Format: | eBook |
| Language: | English |
| Published: |
London :
SAGE Publications, Ltd.,
2017.
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| Online Access: | Connect to the full text of the electronic book |
| Summary: | This dataset example introduces researchers to estimating cross-correlations between two time series variables. A cross-correlation examines the correlation between two time series variables contemporaneously and at various lagged values. Cross-correlations help researchers understand if two variables are related to each other and, if so, whether movement in one variable tends to precede or follow movement in the other. This example uses a subset of data from the United States National Oceanic and Atmospheric Administration (NOAA) Climate at a Glance website, looking specifically at average annual global ocean and land temperatures from 1910 to 2015. Understanding trends in global temperature will help researchers and policy makers better understand potential climate change and plan for its impact. The sample dataset used for this example has been cleaned and organized to make this example easier to follow. Interested readers should read the full documentation for the dataset before using it for research (http://www.ncdc.noaa.gov/cag/time-series/global).Direct Prerequisites: Time Series ACFs and PACFs. |
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| Physical Description: | 1 online resource : illustrations. |
| ISBN: | 9781473995383 1473995388 |