Palisade Corporation

- Statistics and Forecasting Tool Set



StatTools covers the most commonly used statistical procedures, and offers unprecedented capabilities for adding new, custom analyses. StatTools replaces Excel’s built-in statistics functions with its own calculations. The accuracy of Excel’s built-in statistics calculations has often been questioned, so StatTools doesn’t use them. All StatTools functions are true Excel functions, and behave exactly as native Excel functions do. Over 30 wide-ranging statistical procedures plus 9 built-in data utilities include forecasts, time series, descriptive statistics, normality tests, group comparisons, correlation, regression analysis, quality control, nonparametric tests, and more.

StatTools 7 adds new statistical analyses, streamlines regression processes, and now gives you the ability to view any data set using the same interactive charting engine found in @RISK!

Kruskal-Wallis Test
This non-parametric test comparing three or more populations has been added in response to customer demand.

Data Viewer
This allows you to view any Excel data set with the same charting engine used to create @RISK graphs and tables. The Data Viewer can pull from any data source -- no simulation needs to be run. With an easy-to-use, intuitive interface, users can simply select any variable to instantly create graphs with Palisade’s amazing graphing engine—which can then be manipulated, customized, and used for reporting and sharing. You can create histograms, cumulative charts, trend plots, box plots, and more.

Cluster Analysis
Groups similar items within your data, so that items in the same group are more similar than to those in other groups. This helps the user highlight and quantify differences between data points.

Principal Component Analysis
Takes large datasets and reduces the dimensionality, eliminating unimportant details while highlighting strong patterns within the data.

Upgraded Regressions
Setting up dummy variables and other manual processes are a thing of the past. Now, you can perform complex regressions in just a single click.

In addition, more complex relationships in data can be analyzed by using non-linear variable transformations. Moreover, the new StatTools regression analysis will handle big data sets faster than before.

Categorical Bar Charts
New, eye-catching bar chart graphs for categorical variables provide a convenient method for showcasing your results.

First, you define your data in StatTools. Then, you perform any of over 30 different types of analysis on your data set, depending on your situation.

StatTools provides a comprehensive and intuitive data set and variable manager right in Excel. You can define any number of data sets, each with the variables you want to analyze, directly from your data in Excel. StatTools intelligently assesses your blocks of data, suggesting variable names and locations for you. Your data sets and variables can reside in different workbooks, allowing you to organize your data as you see fit. Run statistical analyses that refer to your variables, instead of re-selecting your data over and over again in Excel. StatTools fully supports the expanded worksheet size in Excel 2007-2010. Plus, you can define variables that span multiple worksheets.

Once your data sets have been defined, choose a procedure from the StatTools menu or write your own, custom procedure.  To write your own, StatTools includes a complete, object-oriented, programming interface—the Excel Developer Kit (XDK). Custom statistical procedures may be added using Excel's built-in VBA programming language, which allows you to utilize StatTools's built-in data management, charting and reporting tools.

The statistical procedures available in StatTools come in the following natural groups.

Statistical Inference: This group performs the most common statistical inference procedures of confidence intervals and hypothesis tests.

Forecasting: StatTools gives you several methods for forecasting a time series variable. You can also deseasonalize the data first, using the ratio-to-moving-averages method and a multiplicative seasonality model. Then use a forecasting method to forecast your deseasonalized data, and finally “reseasonalize” the forecasts to return to original units.

The outputs include a set of new columns to show the various calculations (for example, the smoothed levels and trends for Holt’s method, the seasonal factors from the ratio-to-moving-averages method, and so on), the forecasts, and the forecast errors. Summary measures such as MAE, RMSE and MAPE are also included for tracking the fit of the model to the observed data. Finally, several time series plots are available, including a plot of the original series, a plot of the series with forecasts superimposed, and a plot of the forecast errors. In cases using deseasonalized data, these plots are available for the original and deseasonalized series.

Classification Analysis: StatTools provides both discriminant analysis and logistic regression. Discriminant analysis predicts which of several groups a variable will fall in, and logistic regression is a nonlinear type of regression analysis where the response variable is 0 or 1 for “failure” or “success.” You can then estimate the probability of success.

Data Management: This group allows you to manipulate your data set in various ways, either by rearranging the data or by creating new variables. These operations are typically performed before running a statistical analysis.

Summary Analyses: This group allows you to calculate several numerical summary measures for single variables or pairs of variables.

Tests for Normality: Because so many statistical procedures assume that a set of data are normally distributed, it is useful to have methods for checking this assumption. StatTools provides three commonly used checks: Chi-square, Lilliefors, and Q-Q plot.

Regression Analysis: For each of these analyses, the following outputs are given: summary measures of each regression equation run, an ANOVA table for each regression, and a table of estimated regression coefficients and other statistics. In addition, StatTools gives you the option of creating two new variables: the fitted values and residuals. Plus, you can create a number of diagnostic scatterplots.

Quality Control Charts: This set of procedures produces control charts that allow you to see whether a process is in statistical control. Each of the procedures takes time series data and plots them in a control chart. This allows you to see whether the data stay within the control limits on the chart. You can also tell if other nonrandom behavior is present, such as long runs above or below the centerline. Each of these procedures provides the option of using all the data or only part of the data for constructing the chart. Furthermore, each lets you base the control limits on the given data or on limits from previous data.

Nonparametric Tests: Nonparametric tests are statistical procedures which can be used to make successful inferences when there is little available data. They are more robust than many of the widely known parametric hypothesis tests. Nonparametric tests do not always need the parametric assumptions—such as normality—or generalized assumptions regarding the underlying distribution. In most cases, the nonparametric tests are much easier to apply and provide clearer interpretation than traditional parametric tests.

Statistical Inference

  • Sample Size Selection
  • Confidence Interval Analysis
    • OneSample
    • TwoSample
    • PairedSample
    • Hypothesis Tests
    • OneSample
    • TwoSample
    • PairedSample
    • Oneway ANOVA
    • TwoWay ANOVA
  • Chisquare Independence Test
  • Runs Test for Randomness

Forecasting Procedure

  • Moving Averages
  • Exponential Smoothing
  • Seasonality

Classification Analysis

  • Discriminant Analysis
  • Logistic Regression

Data Management

  • Categorical Data
  • Stacked and Unstacked data types
  • Variable Transformations
  • Random Sample Generation
  • Analysis across multiple datasets and worksheets
  • Maximum 1024 datasets with 256 variables per dataset
  • Maximum 16 million data points per variable (StatTools Industrial) or 10,000 data points per variable (StatTools Pro)

Multivariate Analysis

  • Principal Component Analysis
  • Cluster Analysis

Summary Analyses and Graphs

  • OneVariable Summary
  • Correlation/Covariance
  • Autocorrelation
  • Histogram
  • Scatterplot
  • Time Series
  • Box Whisker
  • Bar

Normality Tests

  • Chisquare Test
  • Lilliefors Test
  • QQ Normal Plot

Regression Analysis

  • Simple
  • Stepwise
    • Forward
    • Backward
    • Block

Quality Control

  • XBar Charts
  • R Charts
  • P Charts
  • C Charts
  • U Charts
  • Pareto Charts

Nonparametric Tests

  • The Sign Test
  • WilcoxonSigned Rank Test
  • MannWhitney Test (also known as Wilcoxon RankSum Test)
  • KruskalWallis Test


  • New statistics in Excel
  • Seamless integration with Excel
  • Live updating when input data changes
  • Intelligent data management
  • Capacity for large data sets; support for Excel 2010 and higher worksheet size
  • Excel-based reporting and charting
  • Excel data access
  • Save results in Excel workbooks
  • Data Viewer
  • Excel Developer Kit (XDK)


  • Replaces questionable Excel functions and perform wide range of analyses
  • Never leave your spreadsheet; get up to speed quickly
  • Statistical reports and charts always reflect latest data
  • Quick definition of data sets; management of multiple data sets
  • No limits on amount of data to analyze (Industrial only. 10,000 data points per variable for Professional)
  • Full customization capabilities on all StatTools reports
  • Import data from virtually any source into Excel
  • Share StatTools reports with any Excel user, even if they don’t have StatTools
  • Create presentation-quality, interactive charts from any data source using Palisade graphing engine
  • Programming interface lets you define custom procedures in StatTools using Excel VBA

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