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Yujie Chen|Qining Guo|Tong Ding|Qihui Feng|Dingyue Liu
 
Yujie Chen|Qining Guo|Tong Ding|Qihui Feng|Dingyue Liu
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=<small>Introduction</small>=
 
=<small>Introduction</small>=
 +
----
  
In this paper, we are going to discuss the logistic model of predicting the population and its historical applications on the size of the US population. The population of the United States is the total number of people living in the United States with US citizenship. Population projection is the estimation of the future size of the population.   
+
In this paper, we are going to discuss the logistic model for predicting the population and its historical applications on the size of the US population. The population of the United States is the total number of people living in the United States with US citizenship. Population projection is the estimation of the future size of the population.   
  
# [[Background of Population]]
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Section I will mention the official source and related background of the US population size.
  
Section I will mention the official source and relating background about the size of the US population.  
+
[[Background of Population|Section I. Background of Population]]  
# [[Importance of population projection]]  
+
  
 
Section II will address why population projection is important.
 
Section II will address why population projection is important.
# [[Before logistic model]]
 
  
Section III will briefly go over exponential population model which had great influence on the invention of the logistic population model.
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[[Importance of population projection|Section II. Importance of Population Projection]]
# [[Logistic Models]]  
+
 
 +
Section III will briefly go over exponential population model which used to have a great influence on the invention of the logistic population model.
 +
 
 +
[[Before logistic model|Section III. Before Logistic Model]]  
  
 
Section IV will focus on the logistic model and its derivations.  
 
Section IV will focus on the logistic model and its derivations.  
# [[Failure of the models]]
 
  
Section V will discuss some historical application of the logistic model.
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[[Logistic Models|Section IV. Logistic Models]]
# [[Further information]]  
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 +
Section V will discuss some historical applications of the logistic model.
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 +
[[Failure of the models|Section V. Failure of the Models]]
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Section VI will provide some useful links for interested readers.
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[[Further information|Section VI. Further Information ]]
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Section VII includes citations.
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[[Reference| Section VII. Reference]]  
  
Section VI will
 
# [[Reference]]
 
  
Section VI includes citations.
 
  
 
[[2018_Fall_MA_279_Walther|Back to MA279 Homepage]]
 
[[2018_Fall_MA_279_Walther|Back to MA279 Homepage]]

Latest revision as of 21:54, 2 December 2018

The size of the US Population and the Logistic Model (Mini 3.b)

Yujie Chen|Qining Guo|Tong Ding|Qihui Feng|Dingyue Liu


Introduction


In this paper, we are going to discuss the logistic model for predicting the population and its historical applications on the size of the US population. The population of the United States is the total number of people living in the United States with US citizenship. Population projection is the estimation of the future size of the population.

Section I will mention the official source and related background of the US population size.

Section I. Background of Population

Section II will address why population projection is important.

Section II. Importance of Population Projection

Section III will briefly go over exponential population model which used to have a great influence on the invention of the logistic population model.

Section III. Before Logistic Model

Section IV will focus on the logistic model and its derivations.

Section IV. Logistic Models

Section V will discuss some historical applications of the logistic model.

Section V. Failure of the Models

Section VI will provide some useful links for interested readers.

Section VI. Further Information

Section VII includes citations.

Section VII. Reference


Back to MA279 Homepage

Alumni Liaison

Ph.D. on Applied Mathematics in Aug 2007. Involved on applications of image super-resolution to electron microscopy

Francisco Blanco-Silva