UNISTAT Statistical Software and Microsoft Excel addin
Unistat StandAlone  Unistat Excel Addin  UNISTAT Light  Developer SDK
Talk to us
Want to buy UNISTAT Software? Or Interested in training? Call us..
Table of Contents
 1 UNISTAT Statistical Software and Microsoft Excel addin
 2 What is UNISTAT ?
 3 Who Uses UNISTAT ?
 4 What are UNISTAT Main Features?
 5 UNISTAT Excel AddIn
 6 UNISTAT StandAlone
 7 UNISTAT Light Edition
 8 UNISTAT Graphics Engine
 9 UNISTAT Reporting Results
 10 UNISTAT as Developer’s Tool
 11 UNISTAT Product Comparison Table
 12 UNISTAT Software System Requirement
What is UNISTAT ?
Unistat is a statistical data analysis tool featuring two modes of operation: The Unistat StandAlone user interface is a complete workbench for data input, analysis, and visualization while the Unistat Excel Addin mode extends the features of the mainstream spreadsheet application with powerful analytical capabilities to Microsoft Excel.
Who Uses UNISTAT ?
Unistat's Is popular among biomedicine researchers, social scientists, market researchers, government departments and students. This software enabling them to perform complex data analysis without the need for large manuals and scripting languages.
Unistat is used in both industry and academia. Unistat caters to the statistical analysis and visualization needs of a wide spectrum of users  from absolute beginners to the seasoned analytics experts, and six sigma black belts.
Do I need to be a statistical expert to use Unistat?
Absolutely not! Even if you are not a statistics expert, Unistat makes it easy for you to learn statistics by helping users focus on the analysis results and the impact of the result on a business / practical scenario, rather than spending time on learning formulas and performing complicated statistical calculations.
Which industries use Unistat?
Companies use Unistat to analyse their data, and help improve their processes, get deep insights, design experiments, and solve some of the most difficult problems. Few of the industries using Unistat:
Apparel  Healthcare  Manufacturing 
Automotive  Food and beverage 
Pharmaceuticals

Banking & Insurance  Government 
SemiConductors

Chemicals  Medical Devices  Services 
Energy & Resources  Nonprofit 
What are UNISTAT Main Features?
 Unistat Excel Addin
 Unistat StandAlone
 Graphics
 Reporting
 Developer SDK
 Bioassay addon module
UNISTAT Excel AddIn
Bestpractice statistical data analysis in Microsoft Excel is difficult with existing addins and other software tools. UNISTAT is different, adding the power and accuracy of a fullfeatured statistical package to your existing analysis and visualization workflow.
Using UNISTAT as Excel addin is easy. All you need to do is select a block of data and then select a procedure from the UNISTAT menus. UNISTAT’s procedure dialogues are intuitive to use and you will not feel as if you are dealing with another program.
By default, UNISTAT will create its output in a new Excel worksheet. You will also have the option to send the same output to Word or HTML for the web.
All numeric results from UNISTAT have up to 15digit precision, though you can choose to display them with only the desired number of digits. This prevents the buildup of rounding errors when output from one procedure is used as input for another procedure.
Statistical analysis in Excel
3D Bar Chart  Friedman TwoWay ANOVA  Multinomial Regression  Multiple Comparisons 
Reliability Analysis

3D Histogram  Gauge R&R Analysis  Multiple Comparisons  Multiple Discriminant Analysis  Ribbon Chart 
Analysis of Variance  General Linear Model  Multiple Discriminant Analysis  Multisample Median Test 
Sample Size & Power: ANOVA

Area Chart  Heterogeneity of Regression  Multisample Median Test  Neumann Trend Test 
Sample Size & Power: Correlation

ARIMA  Hierarchical Cluster Analysis  Neumann Trend Test  Nonlinear Regression 
Sample Size & Power: One Sample

Attribute Control Charts  HighLowClose Chart  Nonlinear Regression  Normal Probability Plot 
Sample Size & Power: Phi Distribution

Bar Chart  Histogram  Normal Probability Plot  Normality Tests 
Sample Size & Power: Two Correlations

Binomial Proportion  Holt’s Linear Forecasting  Normality Tests  Outlier Tests 
Sample Size & Power: Two Proportions

BlandAltman Plot  Homogeneity of Variance Tests  Outlier Tests  Page’s L Trend 
Sample Size & Power: Two Samples

BoxCox Regression  Hotelling’s T2 Analysis  Page’s L Trend  Paired Proportions 
Sample Size & Power: Variance

BoxWhisker, Dot and Bar Plots  Hotelling’s T2 Test  Paired Proportions  Paired Samples 
Sample Statistics

BreakDown  Icon Plots  Paired Samples  Parallel Line Method  Scatter Diagram 
Brown’s Exponential Forecasting  Intraclass Correlation Coefficients  Parallel Line Method  Parametric Tests Matrix 
Sequence Diagram

Canonical Correlations  Inverse Fourier Transform  Parametric Tests Matrix  Pareto Chart 
Slope Ratio Method

Chisquare Tests  Jonckheere’s Trend  Pareto Chart  Partial Correlation Matrix 
Spectral Diagram

Cochran’s Q  KMeans Cluster Analysis  Partial Correlation Matrix  PearsonSpearmanKendall Matrix 
Stem and Leaf Plot

Combination of Assays  Kth Neighbour Cluster Analysis  PearsonSpearmanKendall Matrix  Pie Chart 
Stepwise Regression

Confidence Intervals  Kth Neighbour Discriminant Analysis  Pie Chart  Plot & Roots of Polynomials 
Summary Statistics

Contingency Table  KaplanMeier Analysis  Plot & Roots of Polynomials  Plot of 2D Functions 
Survival Comparison Statistics

Correlation Coefficients  Kappa Test InterCategory  Plot of 2D Functions  Plot of 3D Functions  t and FTests 
Cox Regression  Kappa Test InterObserver  Plot of 3D Functions  Plot of Distribution Functions  Table of Means 
Critical Value  Kendall’s Concordance Coeff  Plot of Distribution Functions  Poisson Regression 
Unpaired Proportions

CrossTabulation  KolmogorovSmirnov Tests  Poisson Regression  Polar Plot 
Unpaired Samples

Cumulative Probability  KruskalWallis OneWay ANOVA  Polar Plot  Polynomial Regression 
Variable Control Charts

CylinderPlate 5+1 Assay  Ladder Plot  Polynomial Regression  Principal Components  Weibull Analysis 
Data Transformation  Life Table  Principal Components  Probabilities and Critical Values 
Winters’ Additive Seasonal Forecasting

Equivalence Test for Means  Linear Regression  Probabilities and Critical Values  Process Capability Analysis 
Winters’ Multiplicative Seasonal Forecasting

Expected Frequencies  Logistic Regression  Process Capability Analysis  Quade TwoWay ANOVA  XY Plots 
Factor Analysis  Logit / Probit / Gompit  Quade TwoWay ANOVA  Quantal Response Method  XYZ Grid Plot 
Fan Grid Plot  Matrix Plot  Quantal Response Method  Quantiles 
XYZ Scatter Plot

FourParameter Logistic Regression  Matrix Statistics  Meta Analysis  Random Numbers  XYZ Spin Plot 
Fourier Transform  Meta Analysis  Multidimensional Scaling 
Rectangular Plot


Frequency Distributions  Multidimensional Scaling  Multinomial Regression 
Regression with Replicates

UNISTAT StandAlone
The main advantages of using UNISTAT in standalone mode (i.e. when running independently of Excel) are:
 it does not have the data size restrictions of Excel,
 has advanced data export / import options that are not available in Excel,
 its builtin spreadsheet (Data Processor) provides efficient data handling procedures like:
 Aggregate: compresses large data sets according to the levels of a factor variable
 Recode: assigns new values to the specified value ranges of a variable
 Stack: stacks blocks of data columns and creates an additional factor variable to keep track
 Unstack: separates blocks of data according to the levels of a factor variable
and specialised statistical functions like:
 Rank: computes ranks with ties
 MdRk: computes exact median ranks using the binomial function
 Freq: creates two new variables containing levels and frequencies of a factor variable
 Level: generates a balanced factor variable
 Dummy: generates n dummy variables for a factor variable with n levels
Spreadsheet
UNISTAT comes complete with a fullyfeatured Excellike spreadsheet specialised for statistical data handling.
Data Processor can cater for different types of data such as numeric, date and time, short and long strings, missing and nodata codes.
In standalone mode UNISTAT has practically no limitations on the size of data files. You can handle files with millions of cases and thousands of variables. The only limiting factor is the PC’s memory. In Excel addin mode the data capacity is limited only by Excel. The data capacity of Light Edition is limited by 50 columns and 1500 rows.

Advanced Data Export / Import
Files can be opened, merged or saved in Excel, Access, CSV and a wide range of text file formats.
In addition to the commonly used delimited text (CSV) file format, UNISTAT’s Data Processor supports ASCII by row (or by case, where the first cases of all variables are read first and then the second cases of all variables, etc.) and ASCII by column (or by variable, where all cases in the first variable are read first and then all cases in the second variable, etc.). For further information see User’s Guide section 3.1.0.5. Free Format ASCII Files.

ODBC and SQL
It is possible to open any database for which drivers are installed in the Windows system. It is also possible to execute SQL statements to extract subsets from large databases.
The SQL dialogue allows construction of SQL statements to select a subsample of fields and cases from a database.

UNISTAT Light Edition
Difference between Light and Standard editions
 Data size is limited by 50 columns and 1500 rows
 Available only in the English language
 Macros and developer mode are not available
 The following procedures are not available: meta analysis, nonlinear, logit / probit / gompit, logistic, multinomial, Poisson, BoxCox regressions, Multivariate Analysis (cluster, discriminant, mutidimensional scaling, principal components, factor, reliability) and Time Series Analysis (ARIMA, forecasting, quality control, survival, Fourier analysis) and the optional analysis of bioassays module.
UNISTAT Graphics Engine
Axis Scaling Options
Text Formatting
It is possible to mix different fonts and sub / superscripts in any text object.
You can copy and paste formatted text between UNISTAT text objects and Microsoft Word or other Windows applications.
Titles can be displayed at 0º, 90º, 270º rotations.

Multiple YAxes
Up to five yaxes can be displayed; one on the left and four on the right, allowing representation of diverse data sets on the same graph.
Each axis can be individually controlled with all available scaling options.

Means Plot
XY Plots, Polar Plot, Bar Chart, Area Chart and Ribbon Chart procedures allow plotting the means of the data series with optional error bars. Error bar options include t and Zinterval (at any confidence level), standard error and standard deviation (with userdefined multipliers) and variance. For further information see User’s Guide Section Means Plot.
It is also possible to select a continuous variable for the XAxis, where one or more YAxis variables have multiple values corresponding to the same XAxis variable value. A typical case is the doseresponse plot where there are several response variable values for each dose level.

Error Bars
In addition to the error bar options for means plot, you can define any variable to be displayed as error bars.
This is a powerful feature allowing vertical / horizontal, symmetric / asymmetric error bars for each data point on 2D and 3D scatter plots, bar, area and ribbon charts. For further information see User’s Guide Section Error Bars.

Trend Lines
You can display a line of best fit (linear least squares) for each data series separately.
Confidence interval curves for the mean of Y and / or actual Y values can be drawn at any confidence level.
When only one variable is plotted, it is also possible to fit another curve on the series.

Curve Fitting
Five different types of curves can be fitted on a bivariate plot, Neville, rational, polynomial, exponential and geometric.
Rsquared and standard error values and estimated coefficients are displayed in the legend for polynomial, geometric and exponential fits. It is possible to display residual bars on the graph. For further information see User’s Guide Section Curve Fitting.

Surface Fitting
It is possible to fit 3D surfaces, linear regression planes, polynomial and weighted average surfaces on XYZ scatter plots.
Contour lines of the surface can be shown on either or both of the bottom and top planes. Alternatively, a separate 2D contour map can be drawn with extended annotation possibilities. For further information see User’s Guide Section Surface Fitting.

3D Options
All 3D graphics procedures allow rotation and selection of the view point, as well as selecting one of parallel, onepoint, or threepoint perspectives.
The Spin Plot procedure permits the drawing of an XYZ scatter diagram of three variables and rotation of the plot in all directions in real time.

Interactive Graphics
You can display information about a data point by pressing the and holding the rightmouse button on it. 2D and 3D scatter diagrams, 3D spin, polar, normal probability and regression plots support this feature. In standalone mode, the row of the spreadsheet containing the point is also highlighted simultaneously.
In this way, it is easy to determine which points are outliers in the data set. In regression plots, if the <Delete> key is pressed while a point is highlighted, then this point will be omitted and the graph redrawn with a new regression equation.

UNISTAT Reporting Results
Output to Excel
When Output to Excel button is clicked, output is sent to a new worksheet in the active workbook. Output is formatted in the form of Excel tables directly within Excel and the graphics are in scaleable enhanced metafile format. You can edit the Excel styles created by UNISTAT to change colours and fonts.
All numeric results from UNISTAT have the full 15digit precision, though you can choose to display them with only the desired number of digits. This prevents the buildup of rounding errors when output from one procedure is used as input for another procedure.

Output to Word
UNISTAT does not simply send the old style line printer output to Word. Instead, it reformats its output fully utilising the specific formatting capabilities of Word. When the Output to Word button is clicked, UNISTAT will format its tables directly within Word, in the form of Word tables.
Output is sent to the current document in Word, at the current cursor position. The graphics are in scaleable enhanced metafile format.
You can change the number of digits displayed for numbers from UNISTAT’s Tools / Options dialogue.

Output to the Web
Output is sent to the default web browser in the form of HTML tables and PNG format bitmap images.
The output is styled using CSS, allowing easy integration into web sites, wikis, blogs and other webbased applications.

UNISTAT Output Window
In standalone mode, by default, all output is sent to UNISTAT’s own Output Window. All text output is created in old style line printer format and displayed with a fixedwidth font.
The graphic output is sent to this window in the form of an enhanced metafile object. The Output Window offers all the functionality of WordPad.

UNISTAT as Developer’s Tool
It is possible to run UNISTAT from another application without any part of UNISTAT appearing on the screen. If the developer has an application which requires the use of UNISTAT’s powerful data analysis and graphics procedures, then UNISTAT can be called from within the application in any programming language (C, C++, C#, VB, VBA, Pascal, FORTRAN, etc.), passing data and receiving results. This facility makes UNISTAT a powerful yet flexible programmer’s utility for corporate users and specialised scientific software developers.
When it is run in developers mode, each target PC requires a separate UNISTAT licence.
You can try the Developer SDK for UNISTAT Version while running UNISTAT in demo mode. Please contact Us for a copy.
UNISTAT Product Comparison Table
FEATURES  Light Edition  Standard Edition  Standard Edition + Bioassays Module 

Data Capacity  50 x 1500  * unlimited  * unlimited 
Modes of Running UNISTAT  
StandAlone Mode  
Excel AddIn Mode  
Developer SDK  
Variable Options  
Categorical Data Analysis  
Multiple Dependent Variables  
Creating Interaction Dummy and Lag/Lead Variables  
Output Medium  
UNISTAT Output Window  
Output to Word  
Output to Excel  
Output to Web Browser  
Macros  
Recording Macros  
Running Macros  
Combining Macros  
Macro Shortcut Buttons  
Log File  
Help  
DATA PROCESSOR  
Spreadsheet Functions  
Information  
Transpose Matrix  
Column Sort  
Key Sort  
Matrix Sort  
Recode Column  
Aggregate  
Range Statistics  
Stack Columns  
Unstack Columns  
Format Columns  
Select Row  
Formula  
Mathematical Operators and Functions  
Trigonometric Functions 1  
Trigonometric Functions 2  
Scalar Functions  
Statistical Functions  
Special Functions  
Data Conversion Functions  
Date and Time Functions  
UNISTAT Functions  
Conditional Functions  
Constants  
DATA AND FUNCTION PLOTS  
2D Plots  
XY Plots  
Data Series  
Line  
Symbols  
Error Bars  
Point Labels  
Right YAxes  
Area Enclosed  
Curve Fitting  
Means Plot  
Polar Plot  
Spectral Diagram  
Fan Grid Plot  
3D Plots  
XYZ Scatter Plot  
Viewpoint  
Contours  
XYZ Points  
Planes  
Surface Fitting  
XYZ Grid Plot  
Spin Plot  
Charts  
Pie Chart  
Bar Chart  
Area Chart  
Ribbon Chart  
3D Bar Chart  
HighLowClose Chart  
Plot of Functions  
Plot of 2D Functions  
Plot of 3D Functions  
Plot and Roots of Polynomials  
Plot of Distribution Functions  
DESCRIPTIVE STATISTICS AND DISTRIBUTIONS  
Descriptive Statistics  
Summary Statistics  
Confidence Intervals  
Quantiles (Percentiles)  
Sample Statistics  
Frequency Distributions  
Stem and Leaf Plot  
Sequence Diagram  
Scatter Diagram  
Distribution Functions  
Cumulative Probability  
Critical Value  
Probabilities and Critical Values  
Random Numbers  
Expected Frequencies  
Descriptive Plots  
BoxWhisker, Dot and Bar Plots  
Box and Whisker Plot  
Dot Plot  
Error Bar Plot  
Normal Probability Plot  
Histogram  
3D Histogram  
BlandAltman Plot  
Ladder Plot  
STATISTICAL TESTS CORRELATIONS AND TABLES  
Parametric Tests  
t and FTests  
One Sample tTest  
Pooled Variance tTest  
Separate Variance tTest  
Paired tTest  
FTest  
Levene’s FTest  
Equivalence Test for Means  
Parametric Tests Matrix  
Hotelling’s TSquared Test  
Correlations  
Correlation Coefficients  
Pearson Product Moment Correlation  
Spearman’s Rank Correlation  
Kendall’s Rank Correlation  
Point Biserial Correlation  
PearsonSpearmanKendall Correlations Matrix  
Partial Correlation Matrix  
Intraclass Correlation Coefficients  
Goodness of Fit Tests  
ChiSquare Tests  
One Sample ChiSquare Test  
Two Sample ChiSquare Test  
KolmogorovSmirnov Tests  
One Sample KolmogorovSmirnov Test: Uniform Distribution  
One Sample KolmogorovSmirnov Test: Normal Distribution  
Two Sample KolmogorovSmirnov Test  
Normality Tests  
ShapiroWilk Test  
KolmogorovSmirnov Test  
Cramervon Mises Test  
AndersonDarling Test  
Outlier Tests  
Dixon  
Grubbs  
ESD Generalised Extreme Studentised Deviate  
Nonparametric Tests with One or Two Samples  
Unpaired Samples  
MannWhitney U Test  
HodgesLehmann Estimator (Unpaired)  
WaldWolfowitz Runs Test  
Moses Extreme Reaction Test  
Two Sample Median Test  
Paired Samples  
Wilcoxon Signed Rank Test  
HodgesLehmann Estimator (Paired)  
Sign Test  
Table of Ranks  
Binomial Proportion  
Runs Test  
Binomial Test  
Noninferiority Test  
Superiority Test  
Equivalence Test for Binomial Proportion  
Unpaired Proportions  
Difference Between Unpaired Proportions  
Risk Ratio  
Odds Ratio and Relative Risks  
Paired Proportions  
Difference Between Paired Proportions  
Fisher’s Exact Test  
McNemar Test  
Odds Ratio (Paired)  
Tetrachoric Correlation  
Multisample Nonparametric Tests  
KruskalWallis OneWay ANOVA  
KruskalWallis ANOVA Test Results  
KruskalWallis ANOVA Multiple Comparisons  
Jonckheere’s Trend  
Multisample Median Test  
Multisample Median Test Results  
Median Multiple Comparisons  
Friedman TwoWay ANOVA  
Friedman ANOVA Test Results  
Friedman ANOVA Multiple Comparisons  
Quade TwoWay ANOVA  
Quade ANOVA Test Results  
Quade ANOVA Multiple Comparisons  
Kendall’s Concordance Coefficient  
Page’s L Trend  
Cochran’s Q  
Kappa Test for InterCategory Variation  
Kappa Test for InterObserver Variation  
Tables  
Contingency Table  
CrossTabulation  
Scores  
Tables  
R x C Table Statistics  
Chisquare Tests  
Fisher’s Exact Test  
Measures of Association  
CochranArmitage Trend Test  
Cohen’s Kappa  
2 x 2 Table Statistics  
Stratified Analysis  
Conditional Independence  
Common Odds Ratio and Relative Risks  
Homogeneity of Odds Ratio  
BreakDown  
Sample Size and Power Estimation  
One Sample  
Sample Size in Estimating the Population Mean  
Sample Size in Tests Concerning the Mean  
Minimum Detectable Difference for One Sample  
Power of the Test for One Sample  
Two Samples  
Sample Size in Estimating Two Population Means  
Sample Size in Tests Concerning Two Means  
Minimum Detectable Difference for Two Samples  
Power of the Test for Two Samples  
Variance  
Sample Size for Variance  
Power of the Test for Variance  
Correlation  
Sample Size for Correlation  
Power of the Test for Correlation  
Two Correlations  
Sample Size for Two Correlations  
Power of the Test for Two Correlations  
Two Proportions  
Sample Size for Two Proportions  
Power of the Test for Two Proportions  
ANOVA  
Sample Size for ANOVA  
Maximum Number of Groups for ANOVA  
Minimum Detectable Difference for ANOVA  
Power of the Test for ANOVA  
Phi Distribution  
Inverse Phi Distribution  
Meta Analysis  
REGRESSION AND ANALYSIS OF VARIANCE  
Matrix Statistics  
Regression Analysis  
Linear Regression  
Polynomial Regression  
Stepwise Regression  
Nonlinear Regression  
Logit / Probit / Gompit / Loglog  
Logistic Regression  
Multinomial Regression  
Poisson Regression  
BoxCox Regression  
Analysis of Variance and General Linear Model  
Analysis of Variance  
General Linear Model  
Randomised Block Designs  
Repeated Measures Designs  
Repeated Measures over all Factors  
Repeated Measures over some Factors  
Latin Squares Designs  
Graeco Latin Squares Designs  
SplitPlot Designs  
Nested Designs  
Crossover Designs  
Tests for ANOVA  
Table of Means  
Homogeneity of Variance Tests  
Multiple Comparisons  
StudentNewmanKeuls  
TukeyHSD  
TukeyB  
Duncan  
Scheffe  
Least Significant Difference (LSD)  
Bonferroni (Modified LSD)  
Dunnett  
Regression with Replicates  
Heterogeneity of Regression  
MULTIVARIATE ANALYSIS  
Cluster Analysis  
Hierarchical Cluster Analyses  
Distance Measures  
Distance Matrix  
Hierarchical Methods  
Kth Neighbour Cluster Analysis  
KMeans Cluster Analysis  
Discriminant Analysis  
Multiple Discriminant Analysis  
Stepwise Discriminant Analysis  
Linear Discriminant Analysis  
Canonical Discriminant Analysis  
Kth Neighbour Discriminant Analysis  
Multidimensional Scaling  
Classical Multidimensional Scaling  
Ordinal Multidimensional Scaling  
Principal Components Analysis  
Factor Analysis  
Factoring Methods  
Rotations  
Canonical Correlations  
Reliability Analysis  
Multivariate Plots  
XY Matrix Plot  
XY Rectangular Plot  
Icon Plots  
TIME SERIES ANALYSIS  
BoxJenkins ARIMA  
Differencing Input Options  
Differencing Output Options  
Model Fitting  
Seasonal and Nonseasonal Operators  
Model Fitting Parameters  
Model Output Options  
Forecasting  
Forecasting and Smoothing  
Exponential Weights Moving Average  
Brown’s Exponential  
Holt’s Linear  
Winter’s Additive Seasonal  
Winter’s Multiplicative Seasonal  
Neumann Trend Test  
Quality Control  
Operating Characteristic Curve  
Variable Control Charts  
R Chart  
S Chart  
Variance Chart  
X Bar Chart  
Moving Average Charts  
Standard Moving Average Charts  
Exponential Weights Moving Average Chart  
CUSUM Chart  
Table of Values  
X Chart (LeveyJennings)  
Attribute Control Charts  
C Chart  
U Chart  
Np Chart  
P Chart  
Pareto Chart  
Hotelling’s TSquared Analysis  
Weibull Analysis  
TwoParameter Maximum Likelihood Estimation  
TwoParameter OLS Estimation  
ThreeParameter OLS Estimation  
Process Capability Analysis  
Performance  
Capability Indices with Overall Standard Deviation  
Capability Indices with Pooled Standard Deviation  
Nonparametric Capability Indices  
Capability Histogram  
Data Transformation  
Johnson Transformation  
BoxCox Transformation  
Gauge / Gage R&R Analysis  
Gage R&R Average and Range Method  
Gage R&R ANOVA Method  
Gage R&R Charts  
Survival Analysis  
Survival Analysis Variable Selection  
Life Table  
KaplanMeier Analysis  
Product Limit Survival Table  
Quantiles of Survival Function  
KaplanMeier Plots  
Survival Comparison Statistics  
Wilcoxon Tests: Gehan (Lee Desu) Breslow  
Logrank Test: MantelHaenszel (Peto)  
Cox Regression  
Fourier Analysis  
Fourier Transform  
Inverse Fourier Transform  
ANALYSIS OF BIOASSAYS  
Parallel Line Method  
Validity of Data  
Summary Statistics  
Normality Tests  
Homogeneity of Variance Tests  
Outlier Tests  
BoxWhisker, Dot and Bar Plots  
Normality Plots  
Validity of Assay  
Completely Randomised Design  
Randomised Block Design  
Latin Squares Design  
Twin Crossover Design  
Triple Crossover Design  
Regression  
Comparison of Slopes  
Potency  
Plot of Treatment Means  
Slope Ratio Method  
Validity of Data  
Validity of Assay  
Regression  
Potency  
Plot of Treatments  
Quantal Response Method  
Regression  
Logit  
Probit  
Gompit  
Loglog  
Validity of Assay  
Effective Dose (or Lethal Dose)  
Potency  
Plot of Treatments  
FourParameter Logistic Regression  
4PL EP  
Full Model USP  
Effective Dose  
Predictions with Confidence and Prediction Intervals  
Measures of Variability  
Equivalence Tests  
Outlier Plot  
Homogeneity of Variance Plot  
DoseResponse Plot  
Reduced Model USP  
Parallelism Tests  
Potency  
DoseResponse Plot  
Combination of Assays  
Homogeneity Tests  
Combined Potency EP  
Combined Potency USP  
Plot of Potencies  
Specific Assays  
CylinderPlate 5+1 Assay 
* unlimited: limited only by available system memory.
UNISTAT Software System Requirement
UNISTAT 10 runs on 32bit and 64bit Windows 7, 8, 10 and Windows 20032016 Server. UNISTAT addin runs on Excel 19972013 and 32bit and 64bit Excel 20102019. Unistat 10 is fully compatible with Office 365 desktop.