Analyzing climate data from 1850 to 2015 - A White Paper from XLSTAT

FACEBOOK.png

 

Introduction

The aim of this analysis is to describe, visualize and forecast temperature changes on a global scale. To do this, we use XLSTAT time series analysis. Analyzing temporal data is a specific branch of data and statistical analysis. This type of data is called time series data. We will present various methods that can be used to analyze this type of data.

The data used here are monthly air and ocean temperatures from 1850 to 2015.

Contents

  1. Introduction

  2. Visualizing time series data

  3. Descriptive analysis of time series data

  4. Decomposition of Seasonality in a time series

  5. The Holt-Winters Method

  6. Testing for stationarity

  7. Time Series differencing

  8. Test for Stationarity on the Series Following Differencing

  9. ACF and PACF on the Series Following Differencing for the ARIMA Model

  10. ARIMA Model

  11. Conclusion

 


Latest events

Learn the basics of descriptive statistics, multivariate data analysis, tests and modeling with XLSTAT-Basic+

Learn the basics of descriptive statistics, multivariate data analysis, tests and modeling with XLSTAT-Base

This course forms a hands-on introduction to those statistical methods needed by a sensory scientist.

Latest tweets

🎉 @XLSTAT#newversion 2019.4.1 Discover the latest #features and options ➡️ Demšar Significance Diagram ➡️ Latent S… https://t.co/743UvaLOCO

🎥🎉 Our #Stat Café #youtubechannel just exceeded the 7K subscribers milestone. A big thank you to everyone!… https://t.co/e9zI2LnDRm

🗓 Meet statistical developer and Addinsoft CEO at #DSI2019 from Saturday to Monday in New Orleans, LA. ➡️ Visit the… https://t.co/XcccBgOsHF