Normal distribution, confidence intervals, standard deviation, mean, median, quartile, coefficient of variation, statistical analysis, data dispersion
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Abstract
This document analyzes the distribution of variable Y, comparing theoretical and empirical confidence intervals, and examines measures of central tendency and dispersion.
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[...] The mean (or expectation) is equal to the median: This means that the distribution is centered around a mean value, which is characteristic of a normal distribution. 2. Symmetry of the distribution: When we examine the histogram of the data, we observe a global symmetry of the distribution. In a normal distribution, the probability density curve is symmetric with respect to its mean. 3. The calculated confidence intervals correspond to the 'measured' confidence intervals: When we compared the theoretical confidence intervals calculated from the quantiles of the standard normal distribution with the empirically observed (measured) confidence intervals, we found them to be essentially the same. [...]
[...] The class width is 0.05 for the variable symptom. 3. 4. Here are the proportions calculated for the variable symptoms: =4,48 Sy=0.21 P(4.27 [...]
[...] It is calculated by taking the square root of the variance. The higher the standard deviation, the more dispersed the values are around the mean, and the lower it is, the more the values are grouped around the mean. The range of a variable (here, noted interval) is the difference between the largest and smallest value in a dataset. The coefficient of variation is a statistical measure used to evaluate the relative dispersion or variability of a dataset in relation to its mean. [...]
