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Levi Watson
Levi Watson

NTSYS Pc 2.2 Free: A Comprehensive Guide to Multivariate Data Analysis Software




New! NTSYS Pc 2.2 Free: A Powerful Tool for Multivariate Data Analysis




If you are looking for a software that can help you discover patterns and structures in multivariate data, you might want to check out NTSYS Pc 2.2. This is a new and free version of the popular NTSYSpc software that has been used by researchers and professionals in various fields for over two decades. In this article, we will introduce you to NTSYS Pc 2.2, its main features and benefits, how to download and install it, how to use it for different types of data analysis, and how to get help and support for it. By the end of this article, you will have a clear idea of what NTSYS Pc 2.2 can do for you and how to get started with it.




New! NTSYS Pc 2.2 Free



What is NTSYS Pc 2.2?




NTSYSpc stands for Numerical Taxonomy System for Personal Computers. It is a software package that can be used to perform various types of multivariate data analysis, such as cluster analysis, principal component analysis, factor analysis, multidimensional scaling, canonical correlation analysis, discriminant analysis, Mantel test, and many more. It can handle large datasets with hundreds of variables and thousands of cases, and it can produce graphical outputs such as dendrograms, scatterplots, biplots, ordination diagrams, etc.


NTSYSpc was developed by Applied Biostatistics Inc., a company that specializes in providing software solutions for biostatistics and bioinformatics. The first version of NTSYSpc was released in 1997, and since then it has been updated several times to incorporate new methods and features. The latest version is NTSYSpc 2.21w, which was released in February 2021.


NTSYSpc 2.21w is a free update for those who have valid version 2.2 registrations. It is not a free upgrade from version 2.1 or earlier versions. It runs on Windows 7 or higher, including the 64-bit versions. You will need a version 2.2 password and a registration serial number to install and run this program.


The main features of NTSYSpc 2.21w




NTSYSpc 2.21w has many features that make it a powerful tool for multivariate data analysis. Some of the main features are:


  • It supports various types of data formats, such as ASCII files, Excel files, SPSS files, etc.



  • It allows you to edit and manipulate your data using functions such as transpose, sort, merge, split, recode, etc.



  • It provides over 40 methods for multivariate data analysis, covering topics such as similarity and distance measures, clustering methods, ordination methods, correlation methods, regression methods, classification methods, etc.



  • It produces high-quality graphical outputs that can be exported, copied, or printed in various formats, such as BMP, EMF, EPS, PDF, etc.



  • It has a user-friendly interface that allows you to access the functions and options easily and intuitively.



  • It has a comprehensive user guide and a help file that explain the methods and the usage of the program in detail.



  • It has an online support system that provides additional resources and forums for users to share their questions and experiences.



The benefits of using NTSYSpc 2.21w




NTSYSpc 2.21w is not only a powerful tool for multivariate data analysis, but also a beneficial one for various reasons. Some of the benefits are:


  • It is free for those who have valid version 2.2 registrations. You can download and install it without paying any extra fees.



  • It is compatible with Windows 7 or higher, including the 64-bit versions. You can run it on most modern computers without any compatibility issues.



  • It is flexible and versatile. You can use it for different types of data and analysis, depending on your needs and preferences.



  • It is reliable and accurate. You can trust the results and the outputs that it produces, as they are based on well-established methods and algorithms.



  • It is easy to use and learn. You can master the program quickly and easily, thanks to its user-friendly interface, user guide, help file, and online support system.



How to download and install NTSYSpc 2.21w




If you are interested in using NTSYSpc 2.21w, you will need to download and install it on your computer. Here are the steps to do so:


  • Go to the official website of Applied Biostatistics Inc., https://www.exetersoftware.com/cat/ntsyspc/ntsyspc.html, and click on the "Download" button.



  • Fill in the form with your name, email address, version 2.2 password, and registration serial number. If you do not have these information, you will need to purchase them from the website or contact the customer service.



  • After submitting the form, you will receive an email with a link to download the program. Click on the link and save the file (ntsys221w.exe) on your computer.



  • Run the file (ntsys221w.exe) and follow the instructions to install the program on your computer. You will need to accept the license agreement and choose a destination folder for the program.



  • After the installation is complete, you can launch the program from the Start menu or from the desktop shortcut. You will need to enter your version 2.2 password and registration serial number again to activate the program.



How to use NTSYSpc 2.21w for different types of data analysis




Once you have downloaded and installed NTSYSpc 2.21w on your computer, you can start using it for different types of data analysis. In this section, we will give you a brief overview of some of the most common types of data analysis that you can perform with NTSYSpc 2.21w, and how to do them step by step.


Cluster analysis




Cluster analysis is a method of grouping objects or cases based on their similarity or dissimilarity. It can be used to discover patterns or structures in data, such as natural groups, outliers, or clusters.


To perform cluster analysis with NTSYSpc 2.21w, you will need to follow these steps:


  • Prepare your data in a suitable format, such as an ASCII file or an Excel file. Your data should consist of rows (cases) and columns (variables). Make sure that your data does not contain any missing values or errors.



  • Import your data into NTSYSpc 2.21w by clicking on "File" > "Open" > "Data File" and selecting your data file.



  • Select "Similarity" > "Similarity Coefficients" from the main menu to calculate the similarity or distance matrix for your data. You can choose from various similarity or distance measures, such as Euclidean distance, Manhattan distance, Jaccard coefficient, etc.



  • Select "Cluster Analysis" > "Hierarchical Clustering" from the main menu to perform hierarchical clustering on your similarity or distance matrix. You can choose from various clustering methods, such as single linkage, complete linkage, average linkage, etc.



  • Select "Graphics" > "Graphics" > "Dendrogram" from the main menu to display the dendrogram of your hierarchical clustering. You can adjust the parameters and the appearance of the dendrogram, such as the scale, the labels, the colors, etc.



  • Select "File" > "Save" > "Graphics File" from the main menu to save your dendrogram as a graphics file in various formats, such as BMP, EMF, EPS, PDF, etc.



Principal component analysis




Principal component analysis is a method of reducing the dimensionality of data by transforming the original variables into a smaller number of new variables called principal components. It can be used to simplify data, reveal patterns or trends, or identify outliers or anomalies.


To perform principal component analysis with NTSYSpc 2.21w, you will need to follow these steps:


  • Prepare your data in a suitable format, such as an ASCII file or an Excel file. Your data should consist of rows (cases) and columns (variables). Make sure that your data does not contain any missing values or errors.



  • Import your data into NTSYSpc 2.21w by clicking on "File" > "Open" > "Data File" and selecting your data file.



  • Select "Ordination" > "Principal Components Analysis" from the main menu to perform principal component analysis on your data. You can choose from various options, such as scaling, centering, rotation, etc.



  • Select "Graphics" > "Scatterplot" from the main menu to display the scatterplot of your principal components. You can adjust the parameters and the appearance of the scatterplot, such as the axes, the labels, the symbols, the colors, etc.



  • Select "Graphics" > "Biplots" from the main menu to display the biplots of your principal components. Biplots are graphical representations that show both the cases and the variables on the same plot. You can adjust the parameters and the appearance of the biplots, such as the scale, the labels, the symbols, the colors, etc.



  • Select "File" > "Save" > "Graphics File" from the main menu to save your scatterplot or biplot as a graphics file in various formats, such as BMP, EMF, EPS, PDF, etc.



Factor analysis




Factor analysis is a method of exploring the underlying structure of data by extracting a smaller number of latent variables called factors. It can be used to identify common themes or dimensions in data, or to reduce noise or redundancy in data.


To perform factor analysis with NTSYSpc 2.21w, you will need to follow these steps:


  • Prepare your data in a suitable format, such as an ASCII file or an Excel file. Your data should consist of rows (cases) and columns (variables). Make sure that your data does not contain any missing values or errors.



  • Import your data into NTSYSpc 2.21w by clicking on "File" > "Open" > "Data File" and selecting your data file.



  • Select "Ordination" > "Factor Analysis" from the main menu to perform factor analysis on your data. You can choose from various options, such as method (principal components or principal axis), number of factors, rotation (varimax or promax), etc.



  • Select "Graphics" > "Scree Plot" from the main menu to display the scree plot of your factor analysis. The scree plot shows the eigenvalues of each factor and helps you determine how many factors to retain. You can adjust the parameters and the appearance of the scree plot, such as the scale, the labels, the colors, etc.



  • Select "Graphics" > "Factor Loadings Plot" from the main menu to display the factor loadings plot of your factor analysis. The factor loadings plot shows the correlation between each variable and each factor and helps you interpret the meaning of each factor. You can adjust the parameters and the appearance of the factor loadings plot, such as the axes, the labels, the symbols, the colors, etc.



  • Select "File" > "Save" > "Graphics File" from the main menu to save your scree plot or factor loadings plot as a graphics file in various formats, such as BMP, EMF, EPS, PDF, etc.



Multidimensional scaling




Multidimensional scaling is a method of visualizing the similarity or dissimilarity of objects or cases in a low-dimensional space. It can be used to explore the relationships or patterns in data, or to compare different similarity or distance measures.


To perform multidimensional scaling with NTSYSpc 2.21w, you will need to follow these steps:


  • Prepare your data in a suitable format, such as an ASCII file or an Excel file. Your data should consist of a similarity or distance matrix for your objects or cases. Make sure that your matrix is symmetric and non-negative.



  • Import your data into NTSYSpc 2.21w by clicking on "File" > "Open" > "Data File" and selecting your data file.



  • Select "Ordination" > "Multidimensional Scaling" from the main menu to perform multidimensional scaling on your data. You can choose from various options, such as method (classical or nonmetric), number of dimensions, stress function, etc.



  • Select "Graphics" > "Ordination Diagram" from the main menu to display the ordination diagram of your multidimensional scaling. The ordination diagram shows the configuration of your objects or cases in a low-dimensional space and reflects their similarity or dissimilarity. You can adjust the parameters and the appearance of the ordination diagram, such as the axes, the labels, the symbols, the colors, etc.



  • Select "File" > "Save" > "Graphics File" from the main menu to save your ordination diagram as a graphics file in various formats, such as BMP, EMF, EPS, PDF, etc.



Canonical correlation analysis




Canonical correlation analysis is a method of measuring the linear relationship between two sets of variables. It can be used to test hypotheses about the association between two sets of variables, or to identify the variables that contribute most to the relationship.


To perform canonical correlation analysis with NTSYSpc 2.21w, you will need to follow these steps:


  • Prepare your data in a suitable format, such as an ASCII file or an Excel file. Your data should consist of rows (cases) and columns (variables). You should have two sets of variables that you want to analyze. Make sure that your data does not contain any missing values or errors.



  • Import your data into NTSYSpc 2.21w by clicking on "File" > "Open" > "Data File" and selecting your data file.



  • Select "Correlation Methods" > "Canonical Correlation Analysis" from the main menu to perform canonical correlation analysis on your data. You will need to specify which columns belong to which set of variables. You can also choose from various options, such as scaling, centering, rotation, etc.



  • Select "Graphics" > "Scatterplot Matrix" from the main menu to display the scatterplot matrix of your canonical correlation analysis. The scatterplot matrix shows the pairwise scatterplots of your canonical variables and reflects their correlation. You can adjust the parameters and the appearance of the scatterplot matrix, such as the axes, the labels, the symbols, the colors, etc.



  • Select "File" > "Save" > "Graphics File" from the main menu to save your scatterplot matrix as a graphics file in various formats, such as BMP, EMF, EPS, PDF, etc.



Discriminant analysis




Discriminant analysis is a method of classifying objects or cases into predefined groups based on their characteristics. It can be used to predict the group membership of new cases, or to evaluate the accuracy of the classification.


To perform discriminant analysis with NTSYSpc 2.21w, you will need to follow these steps:


  • Prepare your data in a suitable format, such as an ASCII file or an Excel file. Your data should consist of rows (cases) and columns (variables). You should have one variable that indicates the group membership of each case. Make sure that your data does not contain any missing values or errors.



  • Import your data into NTSYSpc 2.21w by clicking on "File" > "Open" > "Data File" and selecting your data file.



  • Select "Classification Methods" > "Discriminant Analysis" from the main menu to perform discriminant analysis on your data. You will need to specify which column contains the group variable. You can also choose from various options, such as method (linear or quadratic), prior probabilities, validation method, etc.



  • Select "Graphics" > "Classification Plot" from the main menu to display the classification plot of your discriminant analysis. The classification plot shows the distribution of your cases and their predicted group membership in a two-dimensional space. You can adjust the parameters and the appearance of the classification plot, such as the axes, the labels, the symbols, the colors, etc.



  • Select "File" > "Save" > "Graphics File" from the main menu to save your classification plot as a graphics file in various formats, such as BMP, EMF, EPS, PDF, etc.



Mantel test




Mantel test is a method of testing the correlation between two similarity or distance matrices. It can be used to compare different methods of measuring similarity or distance, or to test hypotheses about the relationship between two sets of variables.


To perform Mantel test with NTSYSpc 2.21w, you will need to follow these steps:


  • Prepare your data in a suitable format, such as an ASCII file or an Excel file. Your data should consist of two similarity or distance matrices for your objects or cases. Make sure that your matrices are symmetric and non-negative.



  • Import your data into NTSYSpc 2.21w by clicking on "File" > "Open" > "Data File" and selecting your data file.



  • Select "Correlation Methods" > "Mantel Test" from the main menu to perform Mantel test on your data. You can choose from various options, such as number of permutations, partial Mantel test, etc.



  • Select "Graphics" > "Scatterplot" from the main menu to display the scatterplot of your Mantel test. The scatterplot shows the relationship between the two matrices and reflects their correlation. You can adjust the parameters and the appearance of the scatterplot, such as the axes, the labels, the symbols, the colors, etc.



  • Select "File" > "Save" > "Graphics File" from the main menu to save your scatterplot as a graphics file in various formats, such as BMP, EMF, EPS, PDF, etc.



Other methods and options




The methods and options that we have described above are only some of the most common ones that you can use with NTSYSpc 2.21w. There are many other methods and options that you can explore and apply to your data, such as:


  • Similarity: You can calculate various similarity or distance measures for your data, such as Bray-Curtis, Morisita-Horn, Kulczynski, etc.



  • Cluster Analysis: You can perform various clustering methods for your data, such as K-means, fuzzy clustering, Ward's method, etc.



  • Ordination: You can perform various ordination methods for your data, such as correspondence analysis, canonical correspondence analysis, nonmetric multidimensional scaling, etc.



  • Correlation Methods: You can perform various correlation methods for your data, such as Pearson correlation, Spearman correlation, Kendall correlation, etc.



  • Regression Methods: You can perform various regression methods for your data, such as linear regression, logistic regression, nonlinear regression, etc.



  • Classification Methods: You can perform various classification methods for your data, such as nearest neighbor, linear discriminant analysis, quadratic discriminant analysis, etc.



  • Graphics: You can display various graphical outputs for your data, such as histograms, boxplots, pie charts, bar charts, etc.



  • Data: You can edit and manipulate your data using various functions and options, such as transpose, sort, merge, split, recode, etc.



To access these methods and options, you can use the main menu or the toolbar of NTSYSpc 2.21w. You can also refer to the user guide or the help file for more information and instructions.


How to get help and support for NTSYSpc 2.21w




If you encounter any problems or difficulties while using NTSYSpc 2.21w, or if you have any questions or suggestions about the program, you can get help and support from various sources. Some of the sources are:


The user guide and the help file




The user guide and the help file are two documents that provide detailed information and instructions about NTSYSpc 2.21w. They explain the methods and the usage of the program in a clear and comprehensive way. They also include examples and illustrations to help you understand and apply the program better.


You can access the user guide and the help file by clicking


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