single-value grouping |limit grouping|cutpoint grouping|Lower class limit|Upper class limit|Class width|Class mark|rounding error or roundoff error|Histograms|Dotplots|Stem-and-Leaf

2.3 Organizing Quantitative Data

group quantitative data：

To organize quantitative data, we first group the observations into classes (also known as categories or bins）

single-value grouping |limit grouping|cutpoint grouping

（1）Singlevalue grouping：

1.group quantitative data is to use classes in which each class represents a single possible value

2. is particularly suitable for discrete data in which there are only a small number of distinct values.

（2）Limit Grouping：class limits.

Lower class limit: The smallest value that could go in a class.

Upper class limit: The largest value that could go in a class.

Class width: The difference between the lower limit of a class and the lower limit of the next-higher class.

Class mark: The average of the two class limits of a class.

Guideline：

1. 分类依据要合适
2. 一一对应
3. 宽度一致

（3）Cutpoint Grouping：class cutpoints（对于float？）

lower cutpoint同上 Lower class limit

upper cutpoint同上Upper class limit

rounding error or roundoff error.：由于得到的relative frequencies仅保留有限位数，所以最终sum值有可能小于1。

Lower class cutpoint: The smallest value that could go in a class.

Upper class cutpoint: The smallest value that could go in the next-higher class (equivalent to the lower cutpoint of the next-higher class).

Class width: The difference between the cutpoints of a class.（以数轴为例就是断点cutpoint）

Class midpoint: The average of the two cutpoints of a class.

<Histograms>：同 bar chat但是position the bars in a histogram so that they touch each other

 Note: Some statisticians and technologies use class marks or class midpoints centered under the bars.

图形特点：

1.the frequency histogram and relative-frequency histogram have the same shape（The same vertical scale is used for all relative-frequency histograms—a minimum of 0 and a maximum of 1—making direct comparison easy）

2.single-value grouping label the single value

3.cutpoint grouping label the limit

<Dotplots> are similar to histograms(适用于小数单值数据多的情况，易于构建和使用)

<Stem-and-Leaf>Histograms的抽象版（float？）

40.000,41.000,40.009,40.789使用5列茎叶图

缺点：can be awkward with data containing many digits