"Quantile" Example Sentences
1. In statistics, quantile is a measure of the location of a certain value.
2. The distribution curve was divided into quartiles and each quantile was analyzed.
3. I need to determine the 75th quantile of this dataset.
4. The interquartile range is the difference between the 75th and 25th quantiles.
5. This dataset has a higher median and 90th quantile than the previous one.
6. The 10th quantile value is the point below which 10% of the observations lie.
7. Let's plot a histogram and identify the five-number summary and quantiles.
8. The first quartile can also be expressed as the 25th percentile or the lower quartile.
9. The quantiles of this dataset are consistent with a normal distribution.
10. The second quantile is sometimes called the median or 50th percentile.
11. The third quartile is also known as the upper quartile or the 75th percentile.
12. The fourth quartile is the highest 25% of the data, above the third quartile.
13. Quantiles are frequently used to analyze income distributions in social sciences.
14. The fifth quantile contains the top 20% of the observations, also known as the 80th percentile.
15. I computed the deciles and centiles to have a clearer understanding of the data distribution.
16. The quantiles provide valuable information about the range and shape of a dataset.
17. We computed the 95th quantile to identify outliers and extreme values in the dataset.
18. The cumulative distribution function is a graph showing the quantiles of a dataset.
19. The minimum, first quartile, median, third quartile, and maximum are five common summary statistics computed from the quantiles.
20. Do you know how to calculate the interquartile range and the position of the outliers from the quantiles?
21. Quantiles can also be used in machine learning to evaluate model predictions and error distribution.
22. The quantile-quantile plot is a statistical tool used to compare the distribution of two datasets and determine if they have a similar shape.
23. The standard deviation and variance of a dataset can be computed from the quantiles.
24. The range between the 10th and 90th quantiles is commonly used in finance to indicate potential losses or gains.
25. I computed the empirical cumulative density function from the quantiles and compared it to the theoretical distribution.
26. The box and whisker plot is a graphical representation of the five-number summary and the interquartile range.
27. In big data analysis, the quantiles can be computed using parallel computing techniques to speed up the process.
28. The skewness and kurtosis are measures of the shape of a distribution and can be computed from the quantiles.
29. The quantiles can also be used to compute the mean and mode of a dataset.
30. The quantile regression is a method used in econometrics to analyze the relationship between a dependent variable and several independent variables at different quantiles of the data distribution.
Common Phases
1. Calculate the
quantiles of the data set;
2. Determine the interquartile range using the first and third quartiles;
3. Plot the data using quartile-box plots;
4. Generate a histogram with
quantile lines;
5. Use the median as a measure of central tendency instead of the mean, to reduce outliers' influence;
6. Compare the distribution of two datasets using
quantile-
quantile plots;
7. Estimate the probability of an observation falling below a certain
quantile;
8. Identify outliers that fall below or above the lower and upper
quantile limits, respectively;
9. Create equal-sized groups of a variable based on
quantile ranges;
10. Test for the statistical significance of differences between
quantiles using nonparametric tests.