Some plots in statistical analysis require or can benefit from the use of grouping variables or binning of continuous data. The best way to group continuous data will vary by application. This example describes how to group continuous data to meet the needs of your application. Read More »
Some plots in statistical analysis require or can benefit from the use of grouping variables or binning of continuous data. The best way to group continuous data will vary by application. This example describes how to group continuous data to meet the needs of your application.
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Many analysis tools that are used for hypothesis testing in STATISTICA give a calculated test statistic and a p-value. (For more information about hypothesis testing, see the article, How to Interpret Statistical Analysis Results.) At times, it may be necessary in your hypothesis test to report the test’s critical value. This article describes how to find the critical value for a statistical test. Read More »
Many analysis tools that are used for hypothesis testing in STATISTICA give a calculated test statistic and a p-value. (For more information about hypothesis testing, see the article, How to Interpret Statistical Analysis Results.) At times, it may be necessary in your hypothesis test to report the test’s critical value. This article describes how to find the critical value for a statistical test.
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.
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.