Analyzing climate data from 1850 to 2015 - A White Paper from XLSTAT
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.
Visualizing time series data
Descriptive analysis of time series data
Decomposition of Seasonality in a time series
The Holt-Winters Method
Testing for stationarity
Time Series differencing
Test for Stationarity on the Series Following Differencing
ACF and PACF on the Series Following Differencing for the ARIMA Model
This module focuses on Analysis of Variance, but this technique makes assumptions about the underlying distributions in our data
This course covers the excellent features in XLSTAT for investigating, visualising and modelling data sets with measurements on many variables.
This short course delivered online will show consumer scientists how to set up and learn about the routines available in XLSTAT for relating consumer acceptability to sensory/analytic measures.