Dickey Fullers Test Using Spss
Dickey Fuller Test using SPSS
(Field, 2009, p. 46) SPSS is referred to as a computer application that is used for mining data, authoring of surveys analysis of statistics, carrying out analysis of texts as well as deployment and collaboration. The fundamental features of SPSS include data analysis modules which are inclusive of arithmetical descriptions like plots, frequencies, charts, lists as well as complex procedures in statistics the table on variance analysis (ANOVA). Recently, an increasing endeavor has been made in a bid to establish testing procedures that are efficient to find out whether or not autoregressive root procedure generates a recorded time series. This article seeks to explore the approach and structure of root testing through the SPSS application.
The SPSS computer program is well designed for purposes of conducting a survey to survey research and being a modular product, it requires a base system module to function. Dickey Fuller Test using SPSS is applied in statistics to test whether there is a unit test that is present in an autoregressive model. The test was developed by D.A. Dickey and W. A Fuller and is named after these two statisticians. The two developed this test owing to the fact that there were instances when one would be required to use other models to carry out certain analyses which are unconnected to the Base product. The test includes certain co integration tests that are not found in other SPSS applications.
The Dickey Fuller Test has three main versions of tests to it. The first version is the unit test root test whose, the second one is the unit test root with a drift and the third is the unit root test with drift and deterministic time trend. Each test version has its own critical value which is dependent on the sample size. The tests incapable of distinguishing between the near unit- root processes and the true unit-root processes.
Works Cited
Dickey, D.A. and W.A. Fuller 1979, Distribution of
(Field, 2009, p. 46) SPSS is referred to as a computer application that is used for mining data, authoring of surveys analysis of statistics, carrying out analysis of texts as well as deployment and collaboration. The fundamental features of SPSS include data analysis modules which are inclusive of arithmetical descriptions like plots, frequencies, charts, lists as well as complex procedures in statistics the table on variance analysis (ANOVA). Recently, an increasing endeavor has been made in a bid to establish testing procedures that are efficient to find out whether or not autoregressive root procedure generates a recorded time series. This article seeks to explore the approach and structure of root testing through the SPSS application.
The SPSS computer program is well designed for purposes of conducting a survey to survey research and being a modular product, it requires a base system module to function. Dickey Fuller Test using SPSS is applied in statistics to test whether there is a unit test that is present in an autoregressive model. The test was developed by D.A. Dickey and W. A Fuller and is named after these two statisticians. The two developed this test owing to the fact that there were instances when one would be required to use other models to carry out certain analyses which are unconnected to the Base product. The test includes certain co integration tests that are not found in other SPSS applications.
The Dickey Fuller Test has three main versions of tests to it. The first version is the unit test root test whose, the second one is the unit test root with a drift and the third is the unit root test with drift and deterministic time trend. Each test version has its own critical value which is dependent on the sample size. The tests incapable of distinguishing between the near unit- root processes and the true unit-root processes.
Works Cited
Dickey, D.A. and W.A. Fuller 1979, Distribution of
Cited: Dickey, D.A. and W.A. Fuller 1979, Distribution of the Estimators for Autoregressive Time Series with a Unit Root, Journal of the American Statistical Association, 74, p. 427–431. Enders, W. 2004, Applied Econometric Time Series, Second Edition. John Wiley & Sons: United States. Field, A. (2009). Discovering Statistics Using Spss. London, Sage Publications.