4.1.3 Time series (2): The past, present and future of indicators 时间序列 (二) ：指标的过去现在未来在线视频

第一类的这个绝对时间数列的话
The first type of absolute time series

我们说 还有两个层次的分类
as we know, can be divided into two categories

第一个层次是我们提到的
One is what we have discussed

时期数列和时点指标
periodical series and time-point indicator

那它为什么进行如此的分类
Why do we need to divide it

那跟我们在第一章中学到的这个
In the first chapter of this course, we learned

指标中有提到的一个分类
the division of indicators

就是指标它按照时间这个划分不同
The indicators are divided, based on time

分成时期指标和时点指标
into time-period indicator and time-point indicator

时期指标反映的
Time-period indicator reflects

是总体现象在一定时期内的
the cumulative total of the overall phenomena

累计总量水平的指标
over a certain period

而相对应的时点指标
Correspondingly, the time-point indicator

是反映社会经济现象
is an aggregate indicator that reflects

在某一时刻或某一时点上的
the situation of social economic phenomena

状况的总量指标
at a certain time or time point

所以 特别重要的就是说
Therefore, what is important

有一些时间数列
is that some time series

它非常显著的告诉我们
tell us with clear information

信息就它是一个时点指标
that it is a time-point indicator

比如什么 比如我们说某一瞬间
such as in the expression, at that moment

月初 月末 季初 季末
at the beginning or end of a month, at the beginning or end of a quarter/season

那其实回到
Now let us look at

刚刚这个图表中我们也发现
the table again, and we can see

哪一列中
somewhere in these lists

其实已经非常显著的告诉我们
It shows clearly

它是一个时点指标
it is a time-point indicator

那我相信同学们
I believe most of you

看看这个图
can find that information

应该能够非常快的找出来
quickly from the table

哪一个指标
Which indicator

那我们看到应该是这个年末人口数
Let us look at this list: Total Population at The Year-end

对不对
Right

年末人口数是非常显著的
Total Population at The Year-end is a very distinct

这个时点指标
time-point indicator

因此刚刚这个图表中的这个
In this table we just read

年末人口数
Total Population at The Year-end

它也是非常典型的时点数列
is a very typical time-point series

那在对比这个时期数列和时点数列中
By comparing the time-period series and the time-point series

我们要注意到
we have noticed

它们有非常重要的几个区别
several very important distinctions between them

第一个区别是
One distinction is that

对于时期数列来讲的话
in time-period series

它是存在可加性的
there is an additive property

那我们经常在这个年报中可能会听到
We often hear in the annual report

比如说 这个GDP的总量
phrases, such as total GDP

2014年GDP总量
total GDP in 2014

2015年GDP总量
total GDP in 2015, etc.

那我们想想看GDP总量它是否
Now let us consider whether the total GDP

是一个时期数列
is a time-period series

那非常显著 我们说
Clearly, we know

GDP总量的话它是一个
the total GDP is a

累计的这个概念
concept that describes cumulative

对不对
Right

因为我们在搜集这个
Because when we collect

GDP的数据的时候
the data of GDP

它应该是某一天某一天的相加
it should be the sum of the data

形成一个月的数据
of days in a month

然后一个月一个月的数据相加
and of months in a year

形成一年的数据
to form the yearly data

因此对于时期数列来讲的话
This shows time-period series

它是具有可加性的
has an additive property

而时点指标的话
Time-point indicator we just mentioned

那我们刚刚提到
on the other hand

有一个非常显著的指标
is a very conspicuous indicator

是我们提到的年末人口数
Total population at the year-end

大家都应该非常清楚
we are all aware

对于人口数而言的话
is a very conspicuous time-point indicator

它是非常显著的时点指标
as for the number of population

每一个时间点上都会有
At each time point

新的这个婴儿诞生
there are births of babies

也会有一定数量的人死亡
and a certain number of deaths

所以人口数的话
Consequently, population

是非常典型的这个时点数列
is a very typical time-point series

那其实还有一个非常有意思的
What is also very interesting is

这个例子
the following case

比如说 在座的同学可能有同学
Some of you may have classmates

有这个自行车
who own bicycles

拥有自行车这样的一个指标
Whether the indicator of owning a bicycle

是不是一个时点指标
is a time-point indicator

或是一个时期指标
or a time-period indicator

那它典型的话是一个时点指标
It is a typical time-point indicator

为什么这么讲
Why am I so certain

因为我们说时点指标
Because we know time-point indicator

它是不具备可加性的
does not have the additive property

如果你有一辆自行车你不能说
So, today you own a bicycle

过了一个星期以后
but you cannot say, in a week

你有了七辆自行车
you will own 7 bicycles

因此我们说时点数列
So, we say time-point series

它是没有可加性的
has no additive property

另外一个区别是什么
Another distinction is

我们说时期数列和时点数列的话
as for time-period series and time-point series

它的时间长度跟它这个指标数值
whether their time duration is related to

是否有关系
the indicators

时期数列的话
In time-period series

时期长度跟这个指标数值
the length of time is related to

是存在关系的
indicators

而对于时点数列的话
But in time-point series

它的时期长度跟这个指标数值
its length of time is not related to

是没有关系的
indicators

为什么这么说 因为我们说
Why is it so? Because we have

对于这个刚刚提到这个
mentioned, in the above case

时期数列中重要的例子
of an important time-period series

GDP指标而言
about total GDP

我们说时期越长的话
The longer the time is

GDP数值是越大的
the bigger is the amount of GDP

而对于时点指标
But as for time-point indicator

或者说时点数列来讲的话
or in time-point series

刚刚我举的例子
in the case I just mentioned

那个自行车拥有自行车的数量中
about the number of bicycles

我们也知道
we can see

时点指标它跟这个时间长度
the length of time does not bear any relation

是没有关系的
with the time-point

我们说时间长度越长的话
Even though the duration is lengthened

它不影响我们这个
it has no influence on

时点指标数值的大小
the value of time-point indicators

而在这个层次上还有一个
There is another important concept

非常重要的概念叫这个间隔
in this category called interval

我们说相邻两个时点之间的
We refer to the time duration

这个时间跨度我们称之为
between two time points

这个时点数列的一个间隔
as the interval of time-point series

那我们一般用这个f来进行表示
which we often use “f” to express

这是我们说这个绝对数时间数列
This is what we call absolute time series

第一个层次的分类
This is the first category

那我们说在这个第二个层次分类中
The second category of absolute time series

对于时点数列的话
time-point series

我们还有进一步的进行分类
will go through further division

分成什么
How can we divide it

分成连续时点数列
It is subdivided into continuous time point series

和间断时点数列
and discontinuous time point series

那区别连续时点数列和间断时点数列
There is an important criterion to distinguish

有一个非常重要的一个依据是什么
between continuous and discontinuous time point series

我们说资料天天有的话
When we say there is new data information every day

是我们提到这个连续时点数列
we are talking about continuous time point series

而资料并非天天有的话
When we say the data information cannot be collected any day

我们一般认为它是这个间断时点数列
we agree it is a discontinuous time point series

下面这个图表上也有一个例子
There is an example in the chart below

如何来判断这个连续时点数列
showing how to tell a continuous time point series

和间断时点数列
from a discontinuous time point series

而第二个大类是相对数时间数列
The second type is relative time series

相对数时间数列中
There are six categories

我们说主要有六个类别
in relative time series

一个是这个计划完全相对数
They are relative number of fulfilling plan

结构相对数 比例相对数 比较相对数
constituent ratio, proportional relative number, relative ratio

强度相对数和动态相对数这样六种
intensity relative quantity and relative number in dynamic

那这个概念其实在我们讲这个
The concept has been mentioned

指标中其实已经有提到
in lectures on indicators

所以在这里的话
I will not repeat

我们就不具体在提到
in detail here

那我们说对于相对数之间的数列
For series among the relative numbers

它有个非常重要的问题就是
the very important issues

它的这个各期指标数值
is their indicator values from individual periods

它是不可直接相加的
cannot be added directly

有一个例子
Here is an example

比如说要我们来求一个
Suppose we need to figure out

六年的平均库存销售比的话
the average inventory sales ratio in the past 6 years

那我们说能不能直接相加来进行计算
we cannot do the math by directly adding them

那一般而言我们说
Generally speaking

这是一个非常重要的一个考点
this is an important learning focus

是不能够直接进行相加
We cannot calculate the average inventory sales ratio

来进行求平均库存销售比的
by directly putting the numbers together

它只有一种情况
Only in one case

我们能够直接相加除以
can we directly add the figures together

它这个n个数据
and divide n, the number of figures used

只有什么情况
In what case can we do this

只有我们说当这个销售值
Only when the sales

它是一致的时候
are identical

才能够使用直接相加求这个求平均
can we calculate the average by direct addition

第三个类别是我们说
The third category is what we call

这个平均数时间数列
average time series

那我们说平均数时间数列
We divide average time series

主要分成两类 一个是静态和动态
mainly into two kinds, the static and the dynamic

一般而言我们说从这个
Generally speaking,

咱们这一章时间数列这一章的话
from this chapter of Time Series

它就进入动态平均数这个概念
we have learned the concept of dynamic average

那我们说在描述统计中的话
In our description of statistics

我们一般认为
we generally think

它是个静态平均数的概念
it is a static average

对于平均数时间数列的话
Consequently, the average time series

那它也是各期指标数值
refers to the indicators from individual periods

不能够直接相加的
and cannot be added together directly

那我们要区分了
Now we need to distinguish

什么叫相对数 什么叫平均数
relative number from average

那这个图表上就非常明显
As is shown clearly in the chart

我们看到这有两个指标
there are two indicators

一个是人均GDP
Per capita GDP

还有一个是平均工资
and average wage

那对于这样两个指标
Between these two indicators

什么是平均数
which one is average

什么是相对数
and which one is relative number

虽然它们都是
Although they both

似乎都是平均数的概念
seem to be average in concept

它其实有一个显著的区别
there is a remarkable difference

我们说人均GDP 我们认为它是一种
When we say per capita GDP, we assume it is

相对数时间数列
a relative time series

为什么这么说
Why is it so

因为对于人均GDP而言
Because the numerator and denominator

它这个分子 分母并不是一一对应的
of per capita GDP does not correspond

我们说它跟这个平均数
We say its greatest difference

最大的显著区别是
from average is that

我们在算平均工资的时候
when we calculate average income

我们来想想看
think about it

我们算平均工资是不是每一个工人
in calculating the average income, since every worker

它可能都有工资收入
may have their individual income

那它对应的分母的话
the corresponding denominator

每一个工人都有工资收入
is the wage of every individual worker

因此在计算的过程中
Therefore, in the calculation

分子分母是一一对应的
the numerator and denominator correspond

那有一些人均GDP或者说
Sometimes, when we talk about per capita GDP or

人均病床数
number of hospital beds per capita

我们把它在这个相对数时间数列中
we regard them as intensity relative quantity

把它认为是一种强度相对数
among the relative time series

所以它是显著不是平均数时间数列
which is obviously not an average time series

而是相对数时间数列
It is s relative time series

而这个相对数时间数列跟平均数
The greatest difference

一个最大的区别还是
between relative and average time series

这个分子分母没有一一对应
is whether the numerator and denominator correspond

一般而言我们说
Generally speaking

我们在算人均GDP的时候
when we calculate per capita GDP

我们分子部分
the numerator

是一个GDP的总量 而分母是什么
is the total population of GDP. But what is the denominator

分母是我国人口数的一个总数
The denominator is the total number of national population

然后分子分母一比才是人均GDP
The ratio between this numerator and this denominator makes per capita GDP

因此我们说不是每个人
Therefore, not everyone

它都对应有一个GDP
has a corresponding GDP

而在算平均工资的时候
But in the calculation of average wage

可能是每一个工人都对应了一个工资
every worker may correspond with his own wage

这是我们看到的非常重要的
This is a very decisive factor we can see

我们在区别平均数时间数列
when distinguishing average time series

和相对数时间数列
from relative time series

一个非常重要的一个区别点
A very critical distinction

那我们看看这个最后在我们这一讲中
Now let us come to the last issue

最后一个问题就是
we are going to learn in today’s lecture

这个时间数列的一个这个编制原则
the time series compilation principle

那我们看到刚刚这个表格中
As we can see from the previous chart

我们也发现
we discover

对于一个这个2010年到2015年
in the time duration

这个时间长度 这么一个跨度的话
from 2010 to 2015, the time length

要编制这样以下四列
the following four lists of economic indicators

这个经济指标的话
are compiled

要注意哪些原则 一般来讲我们说
Generally, there are a few principles we need to follow

对于经济指标
As for economic indicators

这个时间长度必须是一致的
the time length must be consistent

并且为了使这个经济指标
In addition, to make sure the economic indicator

具有可比性的话
is comparable

一般我们说间隔也应该也是一致的
we usually require the intervals to be consistent, too

那第二个内容就是在经济指标的这个
The second principle is to keep economic indicators

搜集的过程及展示的过程中
remain in the same aggregate range

必须要保证总量范围是一致
during collection and display

并且经济指标计算价格单位一致
It also requires the economic indicator to use the same price calculating unit

而且经济内容也必须要做到一致
And it requires the economic content to be coherent

那第三个方面特别重要
The third principle is particularly important

就是我们在得到这个经济指标这个
It means in the process to collect the

数值的过程中
values of the economic indicators

计算方法也必须是一致的
the computational method must be consistent, too

做这样以下三个方面我们说
Only by following the three principles we just mentioned

你这样编制出来的时间数列才是
can you compile a time series that is

具备科学性的
scientifically valid

那以上这些内容就是我们提到
This is the introduction to time series

这个时间数列这个概述
that we have learned today