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4.4.1 Analysis of Component Factors: Finding the Truth 构成因素分析:抽丝剥茧寻真相课程教案、知识点、字幕

好 现在我们进入第五讲
Now let's start Lecture 5

时间数列的构成因素分析
compositions of time series

那我们观察了很多很多的
We’ve observed a lot of

这个时间数列
time series

那我们看到
and we see that

在分析较长时间变化周期中这个
in analyzing the changing process

经济指标变化过程中
of economic indicators with a long cycle

它的这个经济指标
why do the economic indicators

为什么会呈现这种变化过程
present such a changing process

让我们考虑一下
Let's think about it

其实在分析的过程中
In the analysis, in fact

我们其实能对这个经济指标
many factors can be identified

能分析出很多很多因素
from the economic indicators

比如说因素A
such as factor A

对这个经济指标影响是什么呢
Its effect on economic indicators

上下波动
is fluctuation

因素B的话可能是一个平缓作用
Factor B may play a moderating role

而因素C的话可能又是一个
while factor C may show the effect

往下的一个趋势的影响
of a downward trend

所以在分析经济指标的过程中
So, in the analysis of economic indicators

我们要把影响的因素把它抽离出来
the influencing factors should be extracted

这就是我们这一讲中所要关注的内容
These are the main content of this lecture

那在很多这个分析过程中
When analyzing

我们实际上
we actually

把这些因素作了一个划分别类
have these factors categorized

那我们说 有这样四大类的这个因素
There are four types of factors

第一类因素叫长期趋势
The first type is called secular trend

也就是说时间数列它随着这个
which is a long-term trend

时间的变化而逐渐增加或减少
of the time series that gradually increases

这个长期变化的趋势
or decreases with time

第二种因素叫季节变动
The second factor is seasonal variation

也就是说时间数列在一年中
which is a time series that

或者在固定时间内呈现出非常明显的
shows obvious regular changes

这个固定规则的变动
over a year or a period of time

它是由时间 季节变动引起的
It is caused by changes in time or seasons

第三类因素叫循环变动因素
The third type is cyclical variation

那我们说 指的是时间数列
The time series is based on

在若干年为一个周期
a period of several years

做一个循环波动这样一个变动
and shows cyclical fluctuations

第四种因素叫随机变动因素
The fourth factor is called random variation

那我们一般指的就是这种不规则变动
or it is generally referred to as erratic variation

也就是说经济社会发展过程中
That is, some uncontrollable and unpredictable factors

有一些你无法控制
in economic and social development

没有办法预测的一些因素
have an impact on the time series

对经济指标的时间数列产生影响
of economic indicators

那这四个因素的话
These 4 factors

我们会用四个不同的字符来进行代替
are represented by 4 letters

长期趋势我们一般用T来进行代替
Generally, secular trend is represented by T

积极变动我们一般用S来进行代替
seasonal variation is represented by S

循环变动我们一般用C 字符C
cyclical variation is represented

来进行代替
by C

而随机变动我们应该用I来进行代替
and random variation is represented by I

那我们看到这个时候的话
Here is a graph

我们有一个图形
that reflects the changes

搜集到的是我国从一定时间长度的
in real estate investment in China

这个房地产投资额的一个变化情况
over a certain period of time

那我们看到 在这个图形中
In this graph, we see that

它非常鲜明的有一个
there is a very clear, upward

向上的一个这个长期趋势 非常明显
secular trend, which is very obvious

那这个实际上同学们
After finishing this lecture

你们回去思考一下
you may think about

在你们现实生活中
if there are any

是不是也有一些长期趋势
secular trends in real life

你想想看
For example

你的大一的每月的生活费
Has your living expenditure

和大二的和现在进行比较的话
gradually increased

是不是逐渐在增长的过程
during first three years of college

那对于长期趋势来讲的话
There is also

还有比较显著的 我们一般提到说
a more significant secular trend

经济社会的发展的话
an indicator for economic

我们说经济的这个水平
and social development

一般从一定程度上来讲的话
in general, to a certain extent

或者说从一定长度
or a certain length

这个时间维度来看的话
in the dimension of time

它的长期趋势都是一个增长的趋势
its secular trend is an increasing trend

那还有一个指标
There is another indicator

也是非常显著的这个
which is also a very significant

明显的这个长期趋势
secular trend

我们大家思考一下看 哪个指标
Please think about which index is it

在前面这个时间数列表中
In fact, it was also mentioned

其实也提到了
in the previous table of time series

对了 我们说这个人口指标
Yes, it is the population

其实也是一个显著的 什么呀
which is a significant index

我们国家的人口指标
Our country's population index

它是显著的一个增长趋势
is also a significant secular trend

对不对
right

所以实际上在这个时间数列中
So, in fact

我们说长期趋势它其实是一个
the effect of secular trend

影响作用特别大
is particularly great

或者说影响比重对于经济指标
or it is a factor that has a greater

以及发展过程中
impact on economic indicators

影响比重特别大的一个因素
and the development processes

那第二个因素
The second factor

就是我们刚刚所提到的这个季节趋势
is seasonal variation just mentioned

那我们这里我们看到
We can see

这里有两个图都来反映的
from these two graphs

是这个季节变动
that reflect the seasonal variation

那我们这一个用的是90平米以下
We use the data of housing investment

这个住房投资的一个变化情况
for houses below 90 square meters

我们发现使用了两年的这个
We find that the seasonal

季节数据的话
and monthly data of two years

发现 月份数据的话
are used here

都体现出了它这个季节的变动
which reflect the seasonal changes

那实际上我们看到
In fact, we can see that

这两年的数据它都是一个什么
the data of the two years

在3 4月份的话是一个高峰
showed a peak during March and April

然后到了第三季度和第四季度
Then, in the third and fourth quarter

逐渐往下 下滑的一个趋势
it gradually declined, showing a downward trend

那实际上我们看到这两个图的话
The general trends demonstrated

它的这个大致趋势是一样
in the two graphs are similar

但是不是完全雷同
but not exactly the same

那其实也告诉我们说
It tells us that

季节变动它可能在某年
seasonal variation may be roughly the same

和另外一年之间 可能趋势大致一样
between two years

但不可能这么完全是一致的
but not exactly the same

但它也体现出一定的这个
But the trend of seasonal variation

季节变动的一个趋势
is reflected to a certain degree

那我们看到第三个因素是什么
The third factor is the cyclical variation

循环变动 这个循环变动的数据
the data of which

就非常难取得了
is very difficult to obtain

因为 在经济社会中
Because, in economic life

循环变动找了非常多数据指标
we have researched a lot of indicators

最后我们选择了这个猪肉价格的指标
Finally, we selected the indicator of pork price

在这个国家统计局的这个50个商品
We have collected data of 50 commodities

50个食品的这个搜集过程中
or 50 foods from the database of National Bureau of Statistics

选择了非常长的一个时间数列
A time series for a very long period was selected

那我们发现
and we found

我首先是把这个时间数列
first of all, by displaying the time series

把它集中的
of a smaller dimension

这个比较小的维度给它展示的话
in a centralized manner

你们会发现这个循环变动的幅度
we found the amplitude of the cyclical variation

强烈一些或者说明显一些
is bigger or is more obvious

那我们看到
We see that

如果我们是把它这个图形
if we extend the graph a little

把它展开一些的话
extending its time

可能这个循环变动
maybe this cyclical variation

它不是那么明显
becomes not so obvious

那实际上在我们现实生活中
In actual life

我们去 当然了可能大家在座的同学
as college students

可能说 同学们可能不一定会去
you may not necessarily

买这个食品
buy these foods

但如果说你以后 步入社会的话
But after graduating from universities

你去购买这些食品一类的商品的话
when you buy commodities like these foods

你会发现对于猪肉商品来讲
you will find that the price of pork products

它确实存在这么一个一年半
indeed has a cycle of

这样一个周期 大概
about one and a half years

它一年半周期之间的话
Within the one-and-a-half-year cycle

它是随着这个猪肉的这个价值的话
the prices of pork

类似在上下波动
fluctuate with the its value

这个概念其实咱们在这个经济学中
In fact, in economics

其实也有学习到
we have learned this concept

就是说我们在讲
that is, the relationship

价格和价值的关系的时候曾经提到过
between price and value is that

价格是随着价值在上下波动的
price fluctuates up and down with value

注意这一点
Please pay attention to this

所以我们循环变动其实也是
So, cyclical variation actually

非常好的体现了这么一个变化的情况
reflects such changes very well

最后一个因素
The last factor

我们说是这个不规则变动
is erratic variation

其实对于这个不规则变动来讲
Actually, for erratic variation

我们就比较难以取得
it is more difficult for us to obtain

这个比较长的一个时间数列一个数据
data of a longer time series

那我举一个比较显著的一个例子
Here is an example

就是我们曾经有感受到
We once observed that

就是我们说2008年
after the Wenchuan earthquake

我们说汶川地震的时候
in 2008

那实际上在汶川地震以后
there was a big change

我们这个四川省
in the data of one index

有一项这个指标数据是变化幅度
of Sichuan Province

是非常大的
The change is huge

你们想想看
Please think about it

可能是什么经济指标变化幅度比较大
what economic indicator may it be

很多同学可能都纷纷在思考
Now, you are thinking about it

那实际上 我们马上直观能想到
Actually, we can easily see that

就是这种大灾大难面前的话
in face of such a catastrophe

什么行业受影响是比较大的
which industry was affected the most

保险行业对不对
The insurance industry, right

所以在那一年这个四川省
so, in 2008, the profit margin

它这个保险行业
of the insurance industry

它这个利润率的这个变化幅度
in Sichuan Province

是很大的
had changed greatly

因为对于这个保险行业来讲的话
For the insurance industry

它受这个不规则的影响
it is greatly affected

变动因素的影响是很大的
by erratic variation

所以我们对于这个不规则因素
Therefore, erratic variation

或者说随机因素的这个界定的话
or random variation mainly includes

主要是战争 政治
wars, politics

还有一些这个气侯
climate changes

或者说一些灾难一些影响
and some disasters

它这种变动方向我们是没有办法
We cannot judge

进行判断的
the direction of changes

所以这种因素的话
so this factor

是难以进行预测的
is difficult to predict

就是比较 当然它这个因素
Of course, sometimes this factor

有些时候对这个经济指标这个影响
is very influential

也是非常大的
with economic indicator

那我们说对于这四个因素而言的话
So, what is the relationship among

它们之间的关系是什么
these four factors

长期趋势它是非常重要的
Secular trend is very important

我们是预测 把握 程度是比较高的
Its predictability is relatively high

季节变动也是我们要去进行研究的
Seasonal variation is also a factor to be researched

而剩下的这两个循环变动
And the remaining two factors

和这个不规则变动
cyclical variation and erratic variation

实际上我们在本科阶段
are actually more difficult to study in depth

它是比较难以去深入研究的
at an undergraduate level

那我们对于这四个因素的话
To analyze these four factors

我们有两种模型来进行分析
we have two models

一种模型是我们看到的这个加法模型
One is the additive model

另外一种模型叫乘法模型
The other is the multiplicative model

那我们看到这个加法模型
In the additive model

它这个关系是什么呢
what is the relationship

也就是说我这四个因素
The relationship among these four factors

是T+S+C+I
is T+S+C+I

那么我们说乘法模型是什么呢
while in the multiplicative model

乘法模型是我们说这个四个因素之间
these four factors

它们是交互影响的
interact with each other

所以它们的关系是T×S×C×I
with their relationship as T×S×C×I

那么我们说在现实生活中
Now, let's think about

我们思考一下看 同学们想想看
whether there are more additive models

究竟是加法模型更多
or more multiplicative models

还是乘法模型更多
in real life

也就是我们考虑一下
That is

这些因素它是交互影响的多
are these factors more interactive

还是相互独立的要更多
or independent

那我想很多同学 想一想看
I believe many of you want to better understand

这个复杂因素之间的关系
the relationship among these complicated factors

其实可能乘法模型它这种
In fact, multiplicative models

普遍性要强一些
are more common

那我们根据这个模型我们知道
Since there are two types of models

如果说 这个时候
if we say

我要去对各个因素来进行测定的时候
we want to measure various factors

那我们说那就会存在两种思路
there are two methods

一种是如果说它这个
If the factors

因素之间是相互独立的话
are independent of each other

那我们说我们就选择这个加法模型
choose the additive model

如果说它这个因素之间
if the factors interact

是相互影响的话
with each other

那就是说我们就选择乘法模型
then we choose the multiplicative model

那乘法模型的话
If the multiplicative model is adopted

如果我知道
Then we say

这个T的一个因素影响的话
the influencing factors of T

它自然等于这个
is equivalent to the time series

经济指标的时间数列(公式如上)
of an economic indicator (formula as the above)

然后如果是加法模型
Then, if an additive model is adopted

那我们说这个T的这个测定的话
we use this economic indicator

那自然就是我们说这个经济指标
to the measure T

(formula as the above)

好 这个是我们看到的
Okay, this is

这个时间数列的构成因素分析
the analysis of the components of the time series

主要是四个方面的因素分析
Mainly 4 factors are included

四个方面的因素
These four factors are

一个是长期趋势
secular trend

第二个是我们说的这个季节变动
seasonal variation

第三个是循环变动
cyclical variation

第四个是不规则变动
and erratic variation

好 这一讲内容结束
Okay, that’s all for this lecture

Learn Statistics with Ease课程列表:

Chapter 1 Data and Statistics

-Introduction

-1.1 Applications in Business and Economics

--1.1.1 Statistics application: everywhere 统计应用:无处不在

-1.2 Data、Data Sources

--1.2.1 History of Statistical Practice: A Long Road 统计实践史:漫漫长路

-1.3 Descriptive Statistics

--1.3.1 History of Statistics: Learn from others 统计学科史:博采众长

--1.3.2 Homework 课后习题

-1.4 Statistical Inference

--1.4.1 Basic research methods: statistical tools 基本研究方法:统计的利器

--1.4.2 Homework课后习题

--1.4.3 Basic concepts: the cornerstone of statistics 基本概念:统计的基石

--1.4.4 Homework 课后习题

-1.5 Unit test 第一单元测试题

Chapter 2 Descriptive Statistics: Tabular and Graphical Methods

-Statistical surveys

-2.1Summarizing Qualitative Data

--2.1.1 Statistical investigation: the sharp edge of mining raw ore 统计调查:挖掘原矿的利刃

-2.2Frequency Distribution

--2.2.1 Scheme design: a prelude to statistical survey 方案设计:统计调查的前奏

-2.3Relative Frequency Distribution

--2.3.1 Homework 课后习题

-2.4Bar Graph

--2.4.1 Homework 课后习题

-2.6 Unit 2 test 第二单元测试题

Chapter 3 Descriptive Statistics: Numerical Methods

-Descriptive Statistics: Numerical Methods

-3.1Measures of Location

--3.1.1 Statistics grouping: from original ecology to systematization 统计分组:从原生态到系统化

--3.1.2 Homework 课后习题

-3.2Mean、Median、Mode

--3.2.1 Frequency distribution: the initial appearance of the overall distribution characteristics 频数分布:初显总体分布特征

--3.2.2 Homework 课后习题

-3.3Percentiles

--3.3 .1 Statistics chart: show the best partner for data 统计图表:展现数据最佳拍档

--3.3.2 Homework 课后习题

-3.4Quartiles

--3.4.1 Calculating the average (1): Full expression of central tendency 计算平均数(一):集中趋势之充分表达

--3.4.2 Homework 课后习题

-3.5Measures of Variability

--3.5.1 Calculating the average (2): Full expression of central tendency 计算平均数(二):集中趋势之充分表达

--3.5.2 Homework 课后习题

-3.6Range、Interquartile Range、A.D、Variance

--3.6.1 Position average: a robust expression of central tendency 1 位置平均数:集中趋势之稳健表达1

--3.6.2 Homework 课后习题

-3.7Standard Deviation

--3.7.1 Position average: a robust expression of central tendency 2 位置平均数:集中趋势之稳健表达2

-3.8Coefficient of Variation

--3.8.1 Variance and standard deviation (1): Commonly used indicators of deviation from the center 方差与标准差(一):离中趋势之常用指标

--3.8.2 Variance and Standard Deviation (2): Commonly Used Indicators of Deviation Trend 方差与标准差(二):离中趋势之常用指标

-3.9 unit 3 test 第三单元测试题

Chapter 4 Time Series Analysis

-Time Series Analysis

-4.1 The horizontal of time series

--4.1.1 Time series (1): The past, present and future of the indicator 时间序列 (一) :指标的过去现在未来

--4.1.2 Homework 课后习题

--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

--4.1.4 Homework 课后习题

--4.1.5 Level analysis: the basis of time series analysis 水平分析:时间数列分析的基础

--4.1.6Homework 课后习题

-4.2 The speed analysis of time series

--4.2.1 Speed analysis: relative changes in time series 速度分析:时间数列的相对变动

--4.2.2 Homework 课后习题

-4.3 The calculation of the chronological average

--4.3.1 Average development speed: horizontal method and cumulative method 平均发展速度:水平法和累积法

--4.3.2 Homework 课后习题

-4.4 The calculation of average rate of development and increase

--4.4.1 Analysis of Component Factors: Finding the Truth 构成因素分析:抽丝剥茧寻真相

--4.4.2 Homework 课后习题

-4.5 The secular trend analysis of time series

--4.5.1 Long-term trend determination, smoothing method 长期趋势测定,修匀法

--4.5.2 Homework 课后习题

--4.5.3 Long-term trend determination: equation method 长期趋势测定:方程法

--4.5.4 Homework 课后习题

-4.6 The season fluctuation analysis of time series

--4.6.1 Seasonal change analysis: the same period average method 季节变动分析:同期平均法

-4.7 Unit 4 test 第四单元测试题

Chapter 5 Statistical Index

-Statistical indices

-5.1 The Conception and Type of Statistical Index

--5.1.1 Index overview: definition and classification 指数概览:定义与分类

-5.2 Aggregate Index

--5.2.1 Comprehensive index: first comprehensive and then compare 综合指数:先综合后对比

-5.4 Aggregate Index System

--5.4.1 Comprehensive Index System 综合指数体系

-5.5 Transformative Aggregate Index (Mean value index)

--5.5.1 Average index: compare first and then comprehensive (1) 平均数指数:先对比后综合(一)

--5.5.2 Average index: compare first and then comprehensive (2) 平均数指数:先对比后综合(二)

-5.6 Average target index

--5.6.1 Average index index: first average and then compare 平均指标指数:先平均后对比

-5.7 Multi-factor Index System

--5.7.1 CPI Past and Present CPI 前世今生

-5.8 Economic Index in Reality

--5.8.1 Stock Price Index: Big Family 股票价格指数:大家庭

-5.9 Unit 5 test 第五单元测试题

Chapter 6 Sampling Distributions

-Sampling and sampling distribution

-6.1The binomial distribution

--6.1.1 Sampling survey: definition and several groups of concepts 抽样调查:定义与几组概念

-6.2The geometric distribution

--6.2.1 Probability sampling: common organizational forms 概率抽样:常用组织形式

-6.3The t-distribution

--6.3.1 Non-probability sampling: commonly used sampling methods 非概率抽样:常用抽取方法

-6.4The normal distribution

--6.4.1 Common probability distributions: basic characterization of random variables 常见概率分布:随机变量的基本刻画

-6.5Using the normal table

--6.5.1 Sampling distribution: the cornerstone of sampling inference theory 抽样分布:抽样推断理论的基石

-6.9 Unit 6 test 第六单元测试题

Chapter 7 Confidence Intervals

-Parameter Estimation

-7.1Properties of point estimates: bias and variability

--7.1.1 Point estimation: methods and applications 点估计:方法与应用

-7.2Logic of confidence intervals

--7.2.1 Estimation: Selection and Evaluation 估计量:选择与评价

-7.3Meaning of confidence level

--7.3.1 Interval estimation: basic principles (1) 区间估计:基本原理(一)

--7.3.2 Interval estimation: basic principles (2) 区间估计:基本原理(二)

-7.4Confidence interval for a population proportion

--7.4.1 Interval estimation of the mean: large sample case 均值的区间估计:大样本情形

--7.4.2 Interval estimation of the mean: small sample case 均值的区间估计:小样本情形

-7.5Confidence interval for a population mean

--7.5.1 Interval estimation of the mean: small sample case 区间估计:总体比例和方差

-7.6Finding sample size

--7.6.1 Determination of sample size: a prelude to sampling (1) 样本容量的确定:抽样的前奏(一)

--7.6.2 Determination of sample size: a prelude to sampling (2) 样本容量的确定:抽样的前奏(二)

-7.7 Unit 7 Test 第七单元测试题

Chapter 8: Hypothesis Tests

-Hypothesis Tests

-8.1Forming hypotheses

--8.1.1 Hypothesis testing: proposing hypotheses 假设检验:提出假设

-8.2Logic of hypothesis testing

--8.2.1 Hypothesis testing: basic ideas 假设检验:基本思想

-8.3Type I and Type II errors

--8.3.1 Hypothesis testing: basic steps 假设检验:基本步骤

-8.4Test statistics and p-values 、Two-sided tests

--8.4.1 Example analysis: single population mean test 例题解析:单个总体均值检验

-8.5Hypothesis test for a population mean

--8.5.1 Analysis of examples of individual population proportion and variance test 例题分析 单个总体比例及方差检验

-8.6Hypothesis test for a population proportion

--8.6.1 P value: another test criterion P值:另一个检验准则

-8.7 Unit 8 test 第八单元测试题

Chapter 9 Correlation and Regression Analysis

-Correlation and regression analysis

-9.1Correlative relations

--9.1.1 Correlation analysis: exploring the connection of things 相关分析:初探事物联系

--9.1.2 Correlation coefficient: quantify the degree of correlation 相关系数:量化相关程度

-9.2The description of regression equation

--9.2.1 Regression Analysis: Application at a Glance 回归分析:应用一瞥

-9.3Fit the regression equation

--9.3.1 Regression analysis: equation establishment 回归分析:方程建立

-9.4Correlative relations of determination

--9.4.1 Regression analysis: basic ideas

--9.4.2 Regression analysis: coefficient estimation 回归分析:系数估计

-9.5The application of regression equation

--9.5.1 Regression analysis: model evaluation 回归分析:模型评价

4.4.1 Analysis of Component Factors: Finding the Truth 构成因素分析:抽丝剥茧寻真相笔记与讨论

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