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Data Analysis with STATA

You're reading from   Data Analysis with STATA Explore the big data field and learn how to perform data analytics and predictive modelling in STATA

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Product type Paperback
Published in Oct 2015
Publisher Packt
ISBN-13 9781782173175
Length 176 pages
Edition 1st Edition
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Toc

Table of Contents (11) Chapters Close

Preface 1. Introduction to Stata and Data Analytics 2. Stata Programming and Data Management FREE CHAPTER 3. Data Visualization 4. Important Statistical Tests in Stata 5. Linear Regression in Stata 6. Logistic Regression in Stata 7. Survey Analysis in Stata 8. Time Series Analysis in Stata 9. Survival Analysis in Stata Index

Code for time series analysis in Stata


Let's understand the Stata code to run the autocorrelation test first. To find autocorrelation, we draw correlograms. The command to draw correlograms is corrgram, for example, take a look at the following:

corrgram fridge_sales, lags(12)

You will get the following output when you run this command:

To explore the different relationships between two given time series, you can leverage the xcorr command.

The following graph depicts the existing correlation between the fridge_sales quarterly growth rate and volume. When you use the xcorr command, you need to type all the independent variables first, followed by the dependent variable:

xcorr fridge_sales volume, lags(10) xlabel(-10(1)10,grid)

At lag 0, you can see that there is a nicely pointed out negative correlation between fridge_sales and the volume of the given model. This implies that the drop in volume causes a continuous and immediate increase in fridge_sales, as shown in the following table:

Now...

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