Histograms visually show the frequencies of data. Similarly, a bivariate histogram shows frequencies across two variables. Read More »
Histograms visually show the frequencies of data. Similarly, a bivariate histogram shows frequencies across two variables.
Read More »
Showing relationships between variables in a scatterplot is a powerful tool for understanding the data. When the scale of the variables are widely different, seeing that variability can become difficult when plotting multiple variables in one plot. STATISTICA offers a Double-Y Graph type, which allows two separate scalings for the Y axis. Read More »
Showing relationships between variables in a scatterplot is a powerful tool for understanding the data. When the scale of the variables are widely different, seeing that variability can become difficult when plotting multiple variables in one plot. STATISTICA offers a Double-Y Graph type, which allows two separate scalings for the Y axis.
STATISTICA offers the ability to re-run or resume an analysis from a workbook. This is especially useful when you need to repeat an analysis or you are interrupted from your analysis and need to pick up where you previously stopped. Read More »
STATISTICA offers the ability to re-run or resume an analysis from a workbook. This is especially useful when you need to repeat an analysis or you are interrupted from your analysis and need to pick up where you previously stopped.
Almost all of STATISTICA’s functionality can be accessed in automation with STATISTICA Visual Basic (SVB). Tasks from opening the data and data management to analysis and graphing can be recorded into SVB macros. With the release of Version 10, graph customizations can also be recorded in a macro. These recorded macros can be further customized to give you the specific analyses and output you need. Read More »
Almost all of STATISTICA’s functionality can be accessed in automation with STATISTICA Visual Basic (SVB). Tasks from opening the data and data management to analysis and graphing can be recorded into SVB macros. With the release of Version 10, graph customizations can also be recorded in a macro. These recorded macros can be further customized to give you the specific analyses and output you need.
A scatterplot shows the relationship between continuous variables. Showing a grouping factor in this plot adds another dimension and can greatly enhance a plot’s usefulness. This article will explore two ways of showing a grouping variable in a scatterplot. The difference between the two methods is the fit line. One method uses one fit for all levels of a grouping factor, but shows the levels with point marker colors and patterns. The other method will fit separate lines for each group. Read More »
A scatterplot shows the relationship between continuous variables. Showing a grouping factor in this plot adds another dimension and can greatly enhance a plot’s usefulness. This article will explore two ways of showing a grouping variable in a scatterplot. The difference between the two methods is the fit line. One method uses one fit for all levels of a grouping factor, but shows the levels with point marker colors and patterns. The other method will fit separate lines for each group.
Many procedures in STATISTICA automatically mark specific cells or blocks of cells in spreadsheets in order to "highlight" results (e.g., unusually high frequencies in a frequency table, statistically significant correlation coefficients in a correlation matrix, or statistically significant effects in an ANOVA table of all effects). In the following spreadsheet, notice that the correlations... Read More »
Many procedures in STATISTICA automatically mark specific cells or blocks of cells in spreadsheets in order to "highlight" results (e.g., unusually high frequencies in a frequency table, statistically significant correlation coefficients in a correlation matrix, or statistically significant effects in an ANOVA table of all effects). In the following spreadsheet, notice that the correlations...
Occasionally in working with graphs in STATISTICA, you may encounter a graph that cannot be drawn. This can be due to a number of possibilities. This article will discuss potential causes of graph rendering issues and solutions to those issues. Read More »
Occasionally in working with graphs in STATISTICA, you may encounter a graph that cannot be drawn. This can be due to a number of possibilities. This article will discuss potential causes of graph rendering issues and solutions to those issues.
Many times when using a scatterplot that contains a high density of points, it is difficult to fully understand the data since some points are obscured by other points. Furthermore, there are many cases where the density of points needs to be understood, but this type of analysis cannot always be accomplished with normal scatterplot techniques. To facilitate solutions to both of these problems, it is possible in STATISTICA 10 to control point transparency in a scatterplot. This example illustrates creating a scatterplot with transparent points in STATISTICA. Read More »
Many times when using a scatterplot that contains a high density of points, it is difficult to fully understand the data since some points are obscured by other points. Furthermore, there are many cases where the density of points needs to be understood, but this type of analysis cannot always be accomplished with normal scatterplot techniques. To facilitate solutions to both of these problems, it is possible in STATISTICA 10 to control point transparency in a scatterplot. This example illustrates creating a scatterplot with transparent points in STATISTICA.
The latest version of R (R 2.12) is recommended for use with STATISTICA 10. Integration with older versions of R is not supported. R 2.12 is the first release to include both 32 and 64-bit versions of R binaries in one distribution, but only the 32-bit version should be used. Support for the 64-bit version will be available in the future. Read More »
The latest version of R (R 2.12) is recommended for use with STATISTICA 10. Integration with older versions of R is not supported.
R 2.12 is the first release to include both 32 and 64-bit versions of R binaries in one distribution, but only the 32-bit version should be used. Support for the 64-bit version will be available in the future.
Selecting variables is typically one of the first steps within an analysis dialog in STATISTICA. When the data set contains a large number of variables, certain tools in STATISTICA, including Variable bundles and Show appropriate variables only, make this selection process easier. A variable bundle is a selection of a set of variables within a spreadsheet used to facilitate repeated selections of that same set of variables in analyses. After a variable bundle is created, the bundle can be selected for analysis instead of individually selecting each required variable. This tool helps both to speed up the variable selection process and to ensure the proper selections are made each time the bundle is used. Read More »
Selecting variables is typically one of the first steps within an analysis dialog in STATISTICA. When the data set contains a large number of variables, certain tools in STATISTICA, including Variable bundles and Show appropriate variables only, make this selection process easier.
A variable bundle is a selection of a set of variables within a spreadsheet used to facilitate repeated selections of that same set of variables in analyses. After a variable bundle is created, the bundle can be selected for analysis instead of individually selecting each required variable. This tool helps both to speed up the variable selection process and to ensure the proper selections are made each time the bundle is used.