![]() Installing the latest version is recommended for all users to improve the performance of our. With this version, you will have access to all our improvements and advanced options. If you are currently using our trial version or have a valid license, you can download version 2021. Our R&D team is constantly working on your feedback and incorporating your ideas or important corrections into new versions of XLSTAT. Installing our new version is recommended for all users. Version 2021.2 will give you access to all the above improvements, advanced options and increase the performance of your software. The Mac version is only available for Excel 2016/2019.Īccess this new feature under the Visualizing data menu. You can use XLSTAT’s flag library if your data corresponds to countries, or you can upload your own images. Bar charts with images (available in all XLSTAT solutions)īuild self-explanatory charts for your presentations by using images as labels and/or as backgrounds.All three can be applied to both numerical and categorical data.Īccess this new feature under the Preparing data menu and the Magic Stick button. There are three possible methods: sequential, random and mapping. Data anonymization (available in all XLSTAT solutions)īefore sharing sensitive private data sets, such as sales records or survey results, you may need to anonymize them.The tool makes it easy to build a decision tree, customize it, compute the gain linked to a decision and display the optimal path.Īccess this new feature under the Decision aid menu. It can be used in simple cases, such as which holiday destination to choose at the lowest cost, as well as for more complex business decisions - such as which countries to sell your products in to maximize profit. This decision aid method will help you evaluate different possible solutions to a problem and select the best option. Decision Trees (available in XLSTAT Marketing & Premium).In the left column the initial values are listed, and in the right column the new ones.XLSTAT 2021.2.2 is now available! What’s new? Mapping table: this table lists the modalities of the variables that have been transformed. If the option "Anonymized variables" has been chosen, then the variable labels are presented in their anonymous form. Available in Excel using the XLSTAT software. Discriminant analysis is a popular explanatory and predictive data analysis technique that uses a qualitative variable as an output. This tutorial will help you set up and interpret a Discriminant Analysis in Excel using XLSTAT. They are displayed in the same order as the original data. Discriminant Analysis tutorial in XLSTAT. It is a statistical method for estimating the sampling distribution of an. Three resampling methods are available: Bootstrap: It is the most famous approach it has been introduced by Efron and Tibisharni (1993). Original data: this table groups together all the selected data as displayed in the datasheet.Īnonymized data: this table groups together all the data that has been anonymized. With XLSTAT, you can apply these methods on a selected number of descriptive statistics for quantitative data. ![]() To complete the tool, you have the option of anonymizing variable labels. This specifies the original value of the variables to be replaced in the left column and the new values in the right column. Here the data is replaced by new values provided by a mapping table. This string is used as many times as the modality appears in the dataset. For qualitative variables, the modalities are replaced by a string of randomly selected characters. Thus they remain in the same scale as the initial data. For a quantitative variable, the values are randomly mixed. This method varies depending on the variable type. The number associated with a modality appears as many times as the modality appears in the dataset, so the resulting file a numerical. The modalities of all selected variables are replaced by a sequentially selected integer starting at 1. XLSTAT allows to transform your quantitative and qualitative data according to three methods. ![]() All three can be applied to both quantitative and qualitative data. It’s a good idea to transform sensitive private data before you share it. There are three possible methods: sequential, random and mapping.
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