The purpose of this article is to explain the process of determining and creating stationarity in time series analysis. Creating a visual plot of data is the first step in time series analysis. Graphical representation of data helps understand it better.
Time series analysis works on all structures of data. It comprises of methods to extract meaningful statistics and characteristics of data. Time series test is applicable on datasets arranged periodically (yearly, quarterly, weekly or daily).
In the previous article on Linear Regression using STATA, a simple linear regression model was used to test the hypothesis. However the linear regression will not be effective if the relation between the dependent and independent variable is non linear.
Data entered in STATA can be classified either as numeric or string type. Associated with each type of data is its storage type i.e. the numbers are stored as byte, int, long, float, or double. STATA takes “float” as the default storage type for its variables.
Do-file is an interface in Stata which allows the researcher to compile all the commands and results at one place. Once the commands are stored in do file, one do not need to enter the command again.
Correlation analysis is conducted to examine the relationship between dependent and independent variables. There are two types of correlation analysis in STATA.