univariate statistical measure

univariate statistical measure

1. Concept: A statistical measure that is applied to a single set of data to summarize or describe a variable.

2. types of measurements

   • measures of central tendency
     • half
     • median
     • fashion
   • measures of dispersion
     • range
     • variance
     • standard deviation
   • shape measurements
     • kurtosis
     • asymmetry
   • position measurements
     • percentiles

3. univariate statistical measure (example)

   • variable: ages of a sample of students
   • measures of central tendencies
     • half: 22 years
     • median: 21 years
     • fashion: 20 years
   • measures of dispersion
     • range: 12 years
     • variance: 16.5 years ^2
     • standard deviation: 4.06 years
   • position measurements
     • kurtosis: 0.7 (leptokurtic)
     • asymmetry: 0.2 (positive bias)
     • percentiles
       • P10:18 years
       • P25:19 years
       • P50: 21 years
       • P75: 24 years
       • P90: 27 years
   • position measurements
     • percentiles
       • P10:18 years
       • P25:19 years
       • P50: 21 year

4. Practical applications

   • By analyzing student age data, we can make conclusions about the age distribution and better understand the composition of the sample.
   • The measures of central tendency (mean, median and mode) allow us to identify which is the most representative or typical value of the ages.
   • Dispersion measures (range, variance and standard deviation) give us information about the dispersion or variability of ages.
   • Shape measures (kurtosis and skewness) tell us whether the age distribution is more pointed or flattened, and whether it has any bias to one side.
   • Percentiles help us identify the values ​​that divide the sample into specific percentages, which can be useful for establishing age ranges.
   • These measures can be applied in different fields, such as demographic studies, market analysis, sociological research, among others.