Submitted by Group 8:
Linzi Chen
Julian Archer
Shiyu Wang
To: Dr. Levine
Project Proposal
STAT 512- Section #2 (TTH/12:00pm-1:15pm)
Date: 10/17 th /2013
1.
Problem Statement
By definition the Gross domestic product (GDP) is an officially recognized index for indicating a country’s standard of living. It is specifically known as the market value obtained when making final consideration of all goods and services produced—within a given period—in a particular country.
Naturally it would be interesting to see what factors (variables) influence the GDP. Hence, our project aims at studying the relationship between the response (GDP) and predictors (Population,
Unemployment rate, Inflation, Export, Import, and Foreign direct investment). More importantly, we want to know if know more than one of the predictor variables helps better the GDP prediction.
Table 1 summarizes the details on these predictor variables.
Table 1: Description of the Predictor Variables
Predictor
Variable (X i
)
Population
Unemployment rate
Inflation
Export
Import
Foreign direct investment
Description
Number of people within a particular country
The percentage of the total labor force that is unemployed but available for seeking employment and willing to work
Inflation as measured by consumer price index reflects the annual percentage change in the cost of the average consumer of acquiring a basket of goods and science that may be fixed or changed at specific intervals
Exports of goods and services represent the value of all goods and other market services provided to the rest of the world
Imports of goods and services represent the value of all goods and other market services received from the rest of the world
Foreign direct investment are the net inflows of investment to acquire a lasting management interest (10 percent or more of voting stock) in an enterprise operating in an economy other than that of the investor
2.
Preliminary Analysis
Unit
Count
Unit
Percent
Percentage
Percentage of GDP
Percentage of GDP
US Dollars
2.1.
Descriptive Analysis
The first thing we will do after acquiring all of the relevant data points for the response and predictor variables is to observe the descriptive summary statistics. This will be accomplished using the UNIVARIATE command in the SAS software package.
2.2.
Correlation Analysis
Next, we will run correlation analyses to determine relationships between individual predictor variables and the response variable. The goal here would be to see which correlations are significant. This will be accomplished using the PROC CORR command in SAS.
2.3.
Significance Testing
Finally, our approach will be to run a multiple regression analysis to observe whether we can reasonably state that knowing one or more predictor variables help us determine the response variable. This will be accomplished using the PROC REG command in SAS.