position measurements

position measurements

1. Position measures are statistical indicators that allow the data to be summarized into one, or divide your distribution into intervals of the same size

2. Importance of Statistical Position Measures

   • They are the first step in the analysis. descriptive. When we want to know information about a phenomenon, we start by collecting data.

3. Non-central position measurements

   • the quartile
     • It is one of the most used and divides the distribution into four equal parts. Thus, there are three quartiles. The lower values ​​of the distribution are located below the first (Q1). Half or median the lower values ​​equal to quartile two (Q2) and the higher ones are represented by quartile three (Q3)
   • the quintile
     • In this case, divide the distribution into five parts. Therefore, there are four quintiles. Furthermore, there is no value that divides the distribution into two equal parts. It is less frequent than the previous one.
   • the decile
     • We are facing a quantile that divides the data into ten equal parts. There are nine deciles, from D1 to D9. The D5 corresponds to the median. On the other hand, the upper and lower values ​​(equivalent to the different quartiles) are located at intermediate points between them.
   • percentile
     • Finally, this quantile divides the distribution into one hundred parts. There are 99 percentiles. It has, in turn, an equivalence with deciles and quartiles.

4. Center position measurements

   • The arithmetic, geometric or harmonic mean
     • There are three central measures that indicate a weighted average of the data. The first is the most used and the best known of the three. The geometric is applied in series that show percentage growth. For its part, the harmonica is useful in the analysis of investments in the stock market.
   • median
     • In this case, this is the most recognizable measure of center position. Divide the distribution into two equal parts. In this way, it expresses the median value, not the mean. It is very useful in variables such as income or salaries, while it is closely related to the mean and some of the quantiles seen.
   • fad
     • This is a central measure of the most frequent values. Therefore, fashion informs us about those that are repeated on more occasions. This measure is very useful in market research when we measure an impression on a product with a likert scale.