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If there are even numbers of data points, then the Method 3 starts off the same as the Method 1 or the Method 2 above and you can choose to include or not include the median as a new datapoint. If you choose to include the median as the new datapoint, then proceed to the step 2 or 3 below because you now have an odd number of datapoints.
The 4-quantiles are called quartiles → Q; the difference between upper and lower quartiles is also called the interquartile range, midspread or middle fifty → IQR = Q 3 − Q 1. The 5-quantiles are called quintiles or pentiles → QU; The 6-quantiles are called sextiles → S; The 7-quantiles are called septiles → SP; The 8-quantiles are ...
For example, they require the median and 25% and 75% quartiles as in the example above or 5%, 95%, 2.5%, 97.5% levels for other applications such as assessing the statistical significance of an observation whose distribution is known; see the quantile entry.
Note that all parameters default to the current date, so for example, the second set of parameters can be left out to calculate elapsed time since a past date: {{Age in years, months, weeks and days |month1 = 1 |day1 = 1 |year1 = 1 }} → 2023 years, 11 months, 2 weeks and 6 days
The longer "month" may be set as the first (5–4–4), second (4–5–4), or third (4–4–5) unit. Its major advantage over a regular calendar is that each period is the same length and ends on the same day of the week, which is useful for planning manufacturing or work shifts.
Quantile regression is a type of regression analysis used in statistics and econometrics. Whereas the method of least squares estimates the conditional mean of the response variable across values of the predictor variables, quantile regression estimates the conditional median (or other quantiles) of the response variable.