XLSTAT PCA output successfully reduced the number of variables into 2 components that explained 90.47% of the total variation of the data set.PCA was conducted to determine the correlations between the abundances of volatile terpenes and thiols and sensory attribute scores in marinated grilled meats, as well as to analyze if there was any clustering based on the type of meat and marination treatments employed. As a case of study, multivariate analysis is used to study the effects of unfiltered beer-based marination on the volatile terpenes and thiols, and sensory attributes of grilled ruminant meats. Interests in XLSTAT as statistical software program of choice for routine multivariate statistics has been growing due in part to its compatibility with Microsoft Excel data format. Principal component analysis (PCA) is an unsupervised multivariate analysis technique that simplifies the complexity of data by transforming them in a few dimensions showing their trends and correlations. ![]() Never tried XLSTAT before? Download your free trial today!Multivariate statistics is a tool for examining the relationship of multiple variables simultaneously. If you are currently using our trial version, you can purchase a license of XLSTAT to access these new features. If you have a valid XLSTAT license with access to maintenance and upgrades, you can download the new version for free. The installation of our new version is recommended for all users. This new version will give you access to all the new features mentioned above. Since the formulas are displayed in the results, you can better understand how your variable has been transformed. Go deeper in your knowledge by understanding how your variable has been transformed. Understand Your Johnson Variable Transformation It’s now possible to display the results for any combination of the four first axes without limiting yourself to the first factorial plan. PREFMAP analyses start with a PCA that creates a collection of synthetic axes. Visualize what is more important to you by viewing the relevant aces when performing Preference Mapping. This option is available in descriptive statistics and ANOVA features. Merge Bar Chart with Scatterplotīuild even more insightful plots as you can now merge bar chart with scatterplot in a single graph – helping you see more information at a glance. Plus, now more than two factors can exist in surface response. Visually interpret the results of your surface response analysis as all the surface plot factors are now displayed in the charts. With this feature, an interpretation message is now displayed after power results. Power can be complicated to interpret for a non-statistician expert, so we’ve added comments to help interpret power in sensory discrimination tests. Interpret Power in Sensory Discrimination Tests Save time with clear, basic results as the number of non-purchase intentions (values below a certain threshold) has been added to the report. ![]() Total Unduplicated Reach and Frequency (TURF) With this feature, it is no longer necessary to randomly try different values. An automatic option (Stuge’s rule) has been implemented to determine a relevant number of bins for histograms. Save time building insightful histograms as you can now automatically determine the number of bins in your histogram with our new option. Learn more about the new release below and update your XLSTAT today to benefit from the new features. ![]() Improve your visualizations, merge charts, and enhance your reports. ![]()
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