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Fig. 2 | BMC Health Services Research

Fig. 2

From: A pilot study of patient satisfaction with a self-completed tablet-based digital questionnaire for collecting the patient’s medical history in an emergency department

Fig. 2

Distribution of the scores of the defined scales. Legend: y-axis: Probability density function for the (Gaussian) kernel density estimation (KDE); x-axis: total score in points (0 = disagree, 1 = rather disagree, 2 = rather agree, 3 = agree). The KDE is a non-parametric technique to estimate the distribution of a variable. A density estimator is an algorithm which seeks to model the probability distribution of the data. The grey line represents a smoothed, continuous estimation of the distribution of the data. In this method, a continuous curve is drawn at every individual data point and all of these curves are then added together to generate a single smooth density estimation. The kernel used is a Gaussian (which produces a Gaussian bell curve at each data point). Figure 2 was generated with the Python 3 library seaborn [30]

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BMC Health Services Research

ISSN: 1472-6963

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