Solved – Percentile vs quantile vs quartile

descriptive statisticsmedianpercentagequantiles

What is the difference between the three terms below?

percentile
quantile
quartile

Best Answer

0 quartile = 0 quantile = 0 percentile

1 quartile = 0.25 quantile = 25 percentile

2 quartile = .5 quantile = 50 percentile (median)

3 quartile = .75 quantile = 75 percentile

4 quartile = 1 quantile = 100 percentile

Related Solutions

Solved – Confidence interval of quantile / percentile of the normal distribution

When you are trying to estimate a quantile from data then you can turn the problem into a binomial problem. For 1,000 data points you want to know what value will have 5% of values below it (population values, the sample is just the estimate) and 95% above it. So you can test each possible value using the binomial (how many of your 1,000 values are below the value you are testing). All the values that would not be rejected given your data constitute the confidence interval.

There is some more detail on Wikipedia or by Googling "quantile confidence interval".

Solved – Model percentiles without quantile regression

Linear regression does not predict the 100th percentile. Linear regression is more akin to predicting a mean, which doesn't translate into "percentiles".

And I just played around with the rq() function in R (in the quantreg package). It does indeed allow you to use interaction effects. Try something like:

m <- rq(y ~ x1 + x2 + x1:x2, tau = 0.75)

Best Answer

Related Solutions

Solved – Confidence interval of quantile / percentile of the normal distribution

Solved – Model percentiles without quantile regression

Related Question