Here we list our experience with the Reports tab in SPSS: From SPSS > Choose Analyze > Reporting > OLAP Cube: Choose the continuous and grouping variables as follows, and choose the statistical ( summary) functions for each continuous variable, default is SUM: Result will be as follows: Unfortunately nothing like the Excel pivot tables.[…]
Here is a list of the forecasting techniques available in SPSS: If we choose Autocorrelation, it will show ACF and PACF statistics:
Quick Wizard for Data Import with SPSS: Start IBM SPSS > Go File > Read Text Data: You will find this wizard:
From the menu >> Choose Correlate: Then choose your variables: You will find the output in the backgound: NxN matrix of correlations.
SAS provides the capability to build regression models to analyze ordinal data correlations and use this model to predict out-of-sample values. Here is the process: Open SAS Studio > Go Tasks > Linear Regression > the following window will open: Input Data settings: Model settings: One can add simple variables to the indepedent variables set.[…]
Data Differencing is achieved by creating a new series which is D = Yt – Y[t-1]. Differencing aims at removing the non-stationarity in the time series, a pre-requisite for using ARIMA models against a time series. Here we explore the configuration of differencing and its impact on ACF and PACF: ARIMA configuration with D=0 Configuration[…]
Installation: Download the SAS Academia package from SAS website. I’m using Oracle VM version here. Open and configure as the picture demonstrates: From your browser: Open localhost:10080/SASStudio/34 You start uploading files by clicking on the upload icon then choosing the files to upload:
This feature enables creating whats known as Pivot tables. From SAS studio, select Statistics > Table Analysis. From Data Tab: From Data section: choose your table. Roles section: Choose the attributes you want to show in your pivot table rows and columns. Strata Variables section: choose the measures to put in the values section. Options[…]