- PAST 4.03 is available to all software users as a free download for Windows 10 PCs but also without a hitch on Windows 7 and Windows 8. Compatibility with this data analyzer software may vary, but will generally run fine under Microsoft Windows 10, Windows 8, Windows 8.1, Windows 7, Windows Vista and Windows XP on either a 32-bit or 64-bit setup.
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PAST is a handy application that lets you easily analyze scientific data by calculating several types of statistical indicators and generating graphs. It offers a comprehensive collection of analysis methods that you can apply with just a few mouse clicks.
With PAST you can easily manipulate data and apply several analysis techniques. To enter data, you can use a text file, a raw data file or an Excel worksheet, from where you can copy the values then paste them into the program.
You can add rows, name the columns and remove data that's not useful for the study before processing the values. There's also the option to define a counter as well as transpose the whole range. You can either subtract the mean value or convert the values to 10-base logarithms in order to transform the data. Data distribution can be normalized using Box-Cox transformations among other methods.
Users can generate a percentile plot or a histogram to get a graphical representation of the experiment's results. Several adjustments are made available for this task, among which there's the possibility to tweak the interval values, overall size and character orientation. Then you can print or export the output.
In the statistics area, you'll find several univariate and multivariate analysis techniques like intraclass correlation and variance analysis among others. PAST can analyze geometric correlation and the data diversity, as well as use linear or polynomial models.
With PAST you can easily manipulate data and apply several analysis techniques. To enter data, you can use a text file, a raw data file or an Excel worksheet, from where you can copy the values then paste them into the program.
You can add rows, name the columns and remove data that's not useful for the study before processing the values. There's also the option to define a counter as well as transpose the whole range. You can either subtract the mean value or convert the values to 10-base logarithms in order to transform the data. Data distribution can be normalized using Box-Cox transformations among other methods.
Users can generate a percentile plot or a histogram to get a graphical representation of the experiment's results. Several adjustments are made available for this task, among which there's the possibility to tweak the interval values, overall size and character orientation. Then you can print or export the output.
In the statistics area, you'll find several univariate and multivariate analysis techniques like intraclass correlation and variance analysis among others. PAST can analyze geometric correlation and the data diversity, as well as use linear or polynomial models.
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