Introduction
Data Prototypes
The Visual Statistics Studio textbooks, guides, and manuals are written by using the method of smallest possible data sets. These data sets are stored under (Data, Univariate Prototypes ), (Data, Bivariate Prototypes ) , (Data, Multivariate Prototypes ).
Saving and Retrieving Data
Initially, the visual Statistics Studio will open with the preloaded variable X [1 2 3 4 5].
Click on the ( Projects, Save Project ) commands. You can delete the variable (Data, Delete) and restore the deleted variable by clicking ( Projects, Retrieve Project ) commands.
Modular Design of the Visual Statistics Studio
The main components of the Visual Statistics Studio are Logical, Scalar, Vector, and Matrix modules. The central module is the Vector module, containing the data matrix and its associated marginal referents (Attributes, Entities), and its associated descriptive statistics. Data shown below were obtained by clicking the ( Designs, Regression Analysis, Multiple egression Analysis with Two Predictor Variables ).
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The vector display uses a non-scrollable canvass window with data and other information painted on it. In the case of large data matrices, only the upper left section of the data matrix is visible on the vector display. In these cases, the entire data matrix and its associated descriptive statistics can be observed by clicking the Modules - Vector command,
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which displays vector module on a scrollable spreadsheet. Most programs within this category, as SPSS or Microsoft Excel, use the vector console type of display. However, if you'll work with the Visual Statistics Studio, you'll soon discover the many advantages the canvass window has to offer.
Data Entry
You can enter variable X [1 2 3 4 5] by selecting (Data, Univariate Prototypes , Continuous Variable) and by clicking either the Append or Replace command.
You can also enter data by clicking the (Data, Enter ) commands.
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By clicking the Accept command or by pressing the CTRL + ALT + I keys, data will be transferred to the vector workspace. Before entering data, make sure that cursor is outside of cells containing numbers. For the above example, before clicking the Accept command, the cursor should be on line 6 (marked with the pencil tip).
Data Prototypes
The Visual Statistics Studio designs, textbooks, guides, and manuals are conceptualized around the method of smallest possible data sets. The data prototypes for the key methods of the general linear model are as follows
| Method | Minimum Set of Variables | Minimum n | Limiting Conditions | Data Prototypes |
| Descriptive Statistics | X | 2 | Data, Univariate Prototypes | |
| Correlation | X Y | 3 | For n equal to 2 r is either -1 or +1 | Data, Bivariate Prototypes |
| Regression | X1 Y | 3 | For n equal to 2 R equals 1 | Data, Bivariate Prototypes |
| Multiple Regression | X1 X2 Y | 4 | For n equal to number of variables R equals 1 | Data, Multivariate Prototypes |
| Canonical Analysis | X1 X2 Y1 Y2 | 5 | For n equal to number of variables rho equals 1 | Data, Multivariate Prototypes |
Thus the minimum n for data sets of the general linear model is 5 with the basic data prototype X [1 2 3 4 5] and variations of the numbers 1 2 3 4 5 as [3 1 2 4 5], [2 3 1 5 4], etc. All basic data prototypes have mean equal to 3 and true variance equal to 2. Data prototypes for specific methods of the general linear model are located under the Designs menu and on the (Project, Open Project Files) menu. Data for distributions and function are stored under the Arguments menu.
Invisible and Implicit Commands
There are several 'invisible' and implicit, unlabelled commands. Select (Information, Information Panel, Invisible Commands) for their description.
