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Principal component analysis (PCA) is the process of computing the principal components and using them to perform a change of basis on the data, sometimes using only the first few principal components and ignoring the rest. PCA is used in exploratory data analysis and for making predictive models.

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Follow the example from Analysis by dimensions (codeunit 424), which exports data to a flat file, that is then afterwards downloaded to client and opened with excel. Excel file formatting is done in only few additional calls, so the performance on RTC is similar to that on classic client.

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In the Tools tab, select Excel Add-Ins ; Figure 3. Excel Add-Ins option in menu. In the Add-ins window, select Analysis Toolpak and click OK. Figure 4. Add-ins window. We have successfully loaded the Analysis Toolpak. Click the Data tab > Data Analysis command to see that the Data Analysis tools are now activated. Figure 5. Output: Load the Analysis Toolpak in Mac. Note: If the Analysis Toolpak is not available in the list of Add-Ins, click Browse to find it.

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Aug 16, 2018 · Analyzing large data sets with Excel makes work easier if you follow a few simple rules: Select the cells that contain the data you want to analyze. Click the Quick Analysis button image button that appears to the bottom right of your selected data (or press CRTL + Q). Selected data with Quick ...

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Here again, Excel wants your data in two columns, one for each treatment level. Give each column a heading. 2. Under the Tools menu select Data Analysis… and choose “t ­Test: Paired Two Sample for Means.” OK. 3. Excel asks you to specify the range of cells containing the data.

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