Regression Report

Paper II- Regression 1
Regression Report
by Student’s Name
University
Professor’s Name
Code + Name of Course
Date

Paper II- Regression 2
Table of Contents
Introduction................................................................................................................ 3
Formulation of Assumptions.................................................................................... 3
The Data Set............................................................................................................... 3
Data Analysis.............................................................................................................. 4
R-squared................................................................................................................ 5
Alpha level (α ¿........................................................................................................ 5
Coefficients............................................................................................................. 6
T statistic................................................................................................................. 7
Conclusion.................................................................................................................. 7

Paper II- Regression 3
Introduction
Regression analysis is a statistical tool used to determine the relationship between two or more
variables. The aim of this paper is conducting linear regression with the use of a single
dependent variable and multiple independent variables. Linear regression uses linear approach in
modelling the relationship between a response and one or more explanatory variables. Linear
regression is categorized into two models; simple and multiple. The former has one explanatory
variable while the latter has two or more explanatory variables. As in our case study, the multiple
linear regression model takes the following general equation:
Y = A +b1 X1 +b2 X2
The dependent variable is represented by Y, A is the Y-intercept, X1 and X2 represent the
explanatory variables with their respective coefficients as b1 and b2.
Formulation of Assumptions
We will foresee the Gross Domestic Product (GDP) of Australia using Public Gross Fixed
Capital Formation (PGFCF) and Total Private Gross Fixed Capital Formation (TPGFCF) using
multiple linear regression analysis. GDP is the dependent variable while PGFCF and TPGFCF
are the two independent variables each with 17 observations.
The Data Set
The data set that aided in this research is from Market Research Reports and Analysis of
Australia which displays the country’s Gross Domestic Product, Public Gross Fixed Capital