The first correlation map uses a blue-red (cold-hot) scale to display the correlations. While this has more meaning when there are many dimensions, we take advantage of this example to show how the maps can be used. Correlation maps allow to visually identify patterns in correlations.
#P value with xlstat software#
XLSTAT is among the few software that generates correlation maps. This is confirmed by the table of the p-values below (p-values < 0.0001). In other words, the risk of rejecting the null hypothesis (coefficient =0) while this is true is less than 5%. For the other criteria it is likely that there is an intermediate optimal level, above which the consumers will show their insatisfaction.Ĭoefficients values in bold are significant at a 0.05 significance level. This suggests that the only criterion for which we have "the more, the better" is the crunchiness. The correlation between the liking scores and the Crunchiness is higher than average with 0.466. The correlations between the liking scores and the attributes are mostly low. Values close to zero reflect the absence of correlation. Negative values indicate negative correlation, and positive values indicate positive correlations. The correlations matrix is then displayed.Ĭorrelation coefficients vary between -1 and 1. The first results are the descriptive statistics for the liking data and the attributes. Interpreting the results of a Spearman correlation coefficient test The computations begin once you have clicked on OK. In the Charts tab, we select the correlations maps we want to display. In the Outputs tab, we choose the results we want to display using the checkbox. As the first row of the table corresponds to headers, we leave the Variable labels option checked.īecause the data are not continuous but ordinal, we choose to use the Spearman correlation coefficient instead of the Pearson correlation coefficient which is the usual one for continuous data. We select the liking scores and the four attributes in the Observations/Variables box. Once you've clicked on the button, the dialog box appears. Setting up a Spearman correlation coefficient testĪfter opening XLSTAT, select the Correlation/Association tests / Correlation tests function. In this tutorial, we use the Correlation/Association tests / Correlation tests tool. However two functions are dedicated to that: the Describing data / Similarity/Dissimilarity matrices feature, and the Correlation/Association tests / Correlation tests feature. Our goal is to check how the attributes are correlated with the liking score.Ĭorrelations are computed in many of the XLSTAT features. Each consumer gave a rating on 1 to 5 scale for four attributes (Saltiness, Sweetness, Acidity, Crunchiness) - 1 means "little", and 5 "a lot" -, and then gave an overall liking score on a 1-10 likert scale. The data used in this example correspond to a survey where a given brand/type of potato chips has been evaluated by 100 consumers. Dataset to run a Spearman correlation coefficient test Not sure this is the statistical test you are looking for? Check out this guide. This tutorial will help you run and interpret a Spearman non parametric correlation test on quantitative variables in Excel using XLSTAT.
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