当前课程知识点:Learn Statistics with Ease > Chapter 3 Descriptive Statistics: Numerical Methods > 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
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我们开始讲数值计算
We will learn numerical computation today
讲数值计算之前我们要明确一个事
At the beginning of this lecture, I would like to remind you
我们的目的是要说明总体
that our purpose here is to describe the population
也就是要反映总体
and reflect the population
要反映总体的话
How to accomplish this mission
从哪些方面来反映
and what should it represent
初学者可能觉得无从下手
are not easy for beginners to grasp
告诉大家
To begin with
只从两个方面反映总体
there are two aspects
就能够把总体比较完整的反映出来
that can reflect the overall situation of the population
哪两个方面
What are they
一个是集中趋势
They are central tendency
一个是离中趋势
and dispersion tendency
我举一个例子
Here is an example
比如说 一个房地产公司
suppose a real-estate company
他想在某个地方进行房地产开发
is looking for property development projects
他就要了解他的潜在客户
He needs to find potential clients
对房产的需求 要求情况
their demand and investment requirements
他就委托一个调查公司进行调查
So the company commissioned a research company to investigate
调查公司给出两个资料
The research company submitted two sets of data
一个就是家庭平均人数2.7个人
One, averagely there are 2.7 members per family
第二个资料就是这个家庭的方差
Two, the variance of family
为0.7平方/人
is 0.7 square per person
这什么意思告诉他们呢
What does the data show
他就告诉你这里的平均数
It shows the average of number
这个地区想买你房子的
of its potential clients in this area
潜在顾客的平均家庭人数算2.7
is 2.7 per household
也就3个人左右
approximate to 3
但是这3个人左右
But this is the average number
每个家庭之间的人数的差别比较大
different from the actual family size
要注意
Keep this in mind
但是这个房地产公司开发的时候
But the real-estate company designs its project
只注意到平均人数
based on the average number only
他就觉得一家三口人
And imaging a two-bedroom apartment
他住两室一厅就比较好
is sufficient for a family of three
所以他大量开发两室一厅的房子
Therefore, two-bedroom apartments
但是最终结果
outnumber
一室一厅和三室一厅开发的比较少
one-bedroom or three-bedroom apartments
最后卖的时候就出了问题
At the time of sale
一室一厅和三室一厅供不应求
the demand for one-bedroom or three-bedroom apartment
两室一厅的人数
exceeds the supply,
要的人数比较少
while the supply of two-bedroom apartment is excessive.
这是为什么呢
How does this happen
他就去问那个调查公司
The company blames the research company
你好像给出来的资料有问题
for giving him the wrong information
他说不是
The research company denies
但你还有一个指标
by saying there is another indicator
你那个0.7平方人
of 0.7 square per person
就是家庭人数 他们的差别很大
representing the difference in household size
它的方差大
There is a big variance
要注意到这里的家庭
This shows that there are
他这里有两个可能
possibilities of
出现两个极端
two extremes
一个是单身家庭的人多
large number of one-person households
二是三代同堂的比较多
and large number of three-generation households
从这个例子上说明一个什么问题
What does this case tell us
说明我们要认识一个总体的话
It tells us that we need two kinds of data
从两个方面来认识
to describe the population
一个是统计的集中趋势
One is central tendency in statistics
总体的集中趋势
the central tendency of the population
第二个就认识总体的离中趋势
The other is dispersion tendency of population
好 现在我们开始来讲
Ok, now let us look at
总体的集中趋势
the central tendency of the population
总体的集中趋势 就是我们说
It is what we call
反映总体的一般水平的指标
the tendency represented by the indicator
所代表的趋势
that reflects the average value of the population
总体的一般水平
The average value of the population
我们讲的一般水平
as we call it
指的就是平均数
is the mean value
当然平均数 它是抽象到它个体差异
The mean value is the middle calculated
得出来的一般水平
by abstracting individual differences
在统计里面平均数又比较多
There are various mean values in statistics
它首先分为动态平均
First, there are consecutive mean
和静态平均数两大类
and static mean
动态平均数是在时间上进行平均
Consecutive mean is abstracted over periods of time
静态平均数是在空间上进行平均
while static mean, in a certain space
那么静态平均数
So, static mean
我们又把它分为两大类
is further divided into
一类是计算平均数
arithmetic mean
一类是位置平均数
and location average
好 现在我们开始讲计算平均数
Now let us learn how to calculate mean value
计算平均数先讲算术平均数
We will start with arithmetic mean
算术平均数它是最简单的
Arithmetic mean is the simplest
使用最多的平均数
and most widely used average
大家平时讲的
In real life
比如说 这些收入
when we say the five of us
大家五个人一起分
split the earnings equally
这个就是属于算术平均
it is a case of arithmetic mean
其它的我们讲的那个平均重量
And the terms average weight
平均年龄等等都是算术平均数
And average age are all arithmetic means
这个平均数它是用它的总体单位数
Arithmetic mean divides the sum of total amount of character value
去除每个单位的标志值总和
by population size
也就是我们那个公式里面讲的
as shown in this formula
(公式如上)
(see the formula above)
用这个公式来进行计算
This formula can calculate arithmetic mean
当然这是简单的算术平均数
This is the simple arithmetic mean
大家可以看例子
Let us look at this example
我们可以运用
We can use
简单算术平均数的方法
simple arithmetic mean formula
对二妞班上的总评成绩计算平均
to calculate the average test scores of Er Niu’s class
大家可以看下面的计算过程
Let me show you the computation
根据我们刚刚学过的
According to what we have learned
计算简单算术平均数的公式
the formula to calculate simple arithmetic mean
我们可以知道x拔
we know the X bar
是等于总体标志总量
is the population mark total amount
除以总体单位总量
divided by population size total amount
用数学表达式表示为(公式如上)
expressed in mathematical expression (the formula above)
这里总体标志总量表示的
the population mark total amount
就是二妞班上所有同学
Is the sum of Statistics test scores
在这次统计学考试的总评分
of all the students in Er Niu’s class
它分别为50+69+73
In other words, it is the sum of 50, 69, 73
一直加到69
and all the way to last on the list, 69
而总体单位总量
The population size total amount
表示的则是二妞班上
is the overall number of test takers
参加这次考试的总人数
in Er Niu’s class
根据这份成绩单我们可以看到
From this school report we can see
在这里n是等于50
n is 50
最后计算结果得到71.54
and the output is 71.54
我们还有加权的算术平均数
And there is also weighted arithmetic mean
加权的算术平均数是什么意思呢
What is weighted arithmetic mean
就是因为出现了
Weighted arithmetic mean
同一个变量值出现了几次
takes into account the frequency of a variable
出现几次 它的权数就是几
The frequency is the weight
进行加权平均
in calculating the weighted mean
所以这个公式就是我们看到的
That is the formula we can see
(公式如上)
(see the formula above)
在这里大家注意了
Please pay attention to this
这里有个重要概念就是权数
It is important to learn the concept of weight
权数的出现将影响到统计
The concept of weight will affect
后面的所有知识
our learning in the following lectures
权数指的是什么
What is weight
宽泛一点讲
Generally speaking
权数是权衡轻重作用的那个数
weight is used to express the relative importance
如果讲具体一点的话
Specifically speaking
它就是讲在计算平均指标的时候
it means in calculating the mean
衡量每一个变量值
the variables are weighted
对平均指标的贡献大小的那个数
to find the value that contributes to the average indicator
这就是权数
the weight
权数在现实生活里面应用的比较广
Weight is also widely used in real life
人大代表投票的时候
When NPC members vote
每个人的权数都是N分之一
they each have a weight of one Nth
每个人都有一票
Everyone has one vote
这时候的权数就相等
and the weight is equal
那平均起来的时候
So, to calculate the mean
其实用简单算术就能算出来
we only need simple arithmetic
但是如果说股票里面的股权的构成
But when it comes to ownership structure in stocks
那时候的每个股东他的权数不相同
the shareholders have different weight
那时候就加权进行平均
That is why we need weighted mean
那时候就体现了权重大小的作用
to show the function of weight here
下面我们试试用加权算术
Now let me show you how to
平均数的方法
calculate weighted arithmetic mean
来对二妞班上这次考试的
to measure the GPA of the test scores
平均成绩进行计算
in Er Niu’s class
根据我们之前所学过的
According to what we have learned
统计分组的方法
about statistical grouping
我们可以得到 按总评分成绩分组
we can form a frequency distribution table
所形成的频数分布表
based on the grouping of test scores
根据这张频数分布表
The frequency distribution table
我们可以很清楚的看到
shows clearly
这里使用的是组距分组的方法
it uses class interval grouping
而组距分组的方法
One of the important characteristics
一个重要的特征是
of class interval grouping
其中的每一个组
is that units here
不是用一个具体的变量值表示
are not expressed in a specific variable value
而是使用变量值的一个区间
but in a variable interval
表示一个组的分组
to indicate the division of a unit
而要显示每一个组的平均水平
But in order to indicate the average level of each unit
就要进一步引入组中值的概念
the concept of class mid-point is used
我们之前已经学过
We have learned in previous lectures
如何对开口组或者是闭口组的
about different ways to calculate
不同的形式来计算组中值
class mid-point in open-end and close-end classes
我们这里很明显显示的是闭口组
the one displayed obviously in a close-end class
也就是运用每一组的下限
So we can use the lower limit
加上每一组的上限除以2
plus the upper limit and divide by 2
得到这一组的组中值
to get the class mid-point
如我们这里第一组50到60
Suppose the first class is from 50 to 60
它的组中值是等于50+60/2=55
its class mid-point is (50+60)/2=55
其它的组中值的计算方法依此类推
And so on and so forth
分别得到65 75 85和95
The class mid-points of other units
这里每一个组的组中值的具体数值
are 65, 75, 85 and 95
实际上就是
This is in fact
加权算术平均数里的小x
the x in weighted arithmetic average
而根据加权算术平均数的公式
According to the formula to calculate weighted arithmetic average
(公式如上)
(See the formula above)
而要得到每一组的xf
the xf in each group
实际上就是用每一组的组中值
is in fact its class mid-point
乘以每一组的人数
times the number of members in each group
通过进一步计算
In this way
我们可以得到每一组的xf
we have calculated the xf of each group
分别等于110 1365 1200
is 110, 1365, 1200
765和190
765 and 190
Σf则等于所有的总人数
Σf is the total number of test takers
等于50
which is 50
最后通过计算得到x拔
And the x bar we have calculated
等于72.6
is 72.6
大家可以看到在这里
We can check the output
我们使用加权算术平均数
of weighted arithmetic average
所得到的结果
by calculation
和我们前面运用简单算术平均数
It is not the same number
所得到的结果71.54
as the output we got from simple arithmetic average
是不一样的
71.54
那么同学有没有想过
Do any of you wonder
为什么两者前后是不一样的呢
why there are two outputs
其实这里的关键就在于这个组中值
The key is the class mid-point
它表示的只是这一组数据的平均值
It shows the average value of the data in this set
它不能准确的表示这一组的
It cannot show the accurate
具体的数值
specific value of this set
下面我们再来简要介绍一下
At last, let us look at
算术平均数的数学性质
the mathematical quality of arithmetic mean
第一 算术平均数
Firstly, arithmetic mean
与总体单位数的乘积
multiplies population size
等于各标志值的总和
is equal to the total amount of its character value
用数学表达式表示为
In mathematical expression
(公式如上)或者说是
it is (see the formula above) or
(公式如上)
(see the formula above)
第二个数学性质为
The second mathematical quality
每个标志值加或减一个任意常数a
is for every character value to plus or minus an arbitrary constant a
则算术平均数也增加或减少
Consequently, the arithmetic mean is increased or decreased
一个任意常数a
by an arbitrary constant a
三 每一个标志值乘以或除以
Thirdly, every character value multiplies and is divided by
一个任意常数a
an arbitrary constant a
则算术平均数也乘以或除以a
Consequently, the arithmetic mean multiplies or is divided by a
第四个数学性质非常重要
The fourth mathematical quality is very important
它表示的是各标志值
It reveals that the sum of character values
与其算术平均数的离差之和等于零
and arithmetic mean dispersion is zero
如果我们对刚刚的
If we represent the mathematical quality
算术平均数的数学性质
of arithmetic mean
用数学表达式来表示
in mathematical expression
也就是(公式如上)或者是
it is (see the formula above) or
(公式如上)
(see the formula above)
下面我们来看一下
Now let us look at the
具体的论证过程
detailed reasoning
这里可以看到
We can see here
通过将(公式如上)展开
by expanding the (formula above)
可以得到(公式如上)
we can get (formula above)
又由于(公式如上)
and because of (formula above)
再进一步可以得到
we can again get
(公式如上)
(formula above)
最后得到零
and at last, the output, zero
同理我们也可以证明得到
Similarly, we can also prove
(公式如上)
(formula above)
进一步得到(公式如上)
can lead to (formula above)
最后结果也是零
and the output is also zero
-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
-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
-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
--3.2.2 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
-3.9 unit 3 test 第三单元测试题
-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
-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
-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
-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
-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
-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