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Pages:
6 pages/≈1650 words
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6 Sources
Style:
APA
Subject:
Mathematics & Economics
Type:
Statistics Project
Language:
English (U.S.)
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MS Word
Date:
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$ 31.1
Topic:

Data Science Project Report

Statistics Project Instructions:

Tutors who receive orders need to master Python skills and relevant knowledge of financial economics

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DATA SCIENCE PROJECT REPORT
Subject title and code: Global Economic Environment (AF2602)
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Data Science Project Report
In this report, and to calculate the sample size, mean and standard deviation, in addition to the setting of hypotheses, and estimating the fixed-effect model by a Python program, we shall collect data from WDI for the dependent variable, which is Imp. of g&s as a % of GDP, while the four independent variables are; Cab as a % of GDP, Inflation Consumer Price Index, Population, and Money Supply Growth. We shall conclude by testing the hypotheses one by one, and explaining why each is or is not supported by the findings.
The following table represents the list of samples of countries, period, size, mean, and standard deviation. The data is extracted from Databank, World Development Indicators, WDI (The World Bank, 2021). The sample size is 100, the sample mean is 41263051.96, and the standard deviation is75488830.3.
Sample size

 

 

 

 

 

 


100

 

 

 

 

 

Sample mean

 

 

 

 

 

 


41263051.96

 

 

 

 

 

Sample Standard deviation

 

 

 

 

 

 


75488830.3

 

 

 

 

 

Sample period

Sample country

Current Account Bal_gdp

inflation_cpi

Population

Money Supply_growth

Imports g&s (% of GDP)

















2010

Australia

-3.9012953

2.918340027

22031750

10.1307768

20.83966397


2011

Australia

-3.181266533

3.303850156

22340024

7.967777688

20.47031601


2012

Australia

-4.170542032

1.762780156

22733465

7.347916752

21.72951827


2013

Australia

-3.037241645

2.449888641

23128129

6.747131992

21.25226273


2014

Australia

-2.957266065

2.487922705

23475686

7.0328977

21.46703534


2015

Australia

-4.213876251

1.508366722

23815995

5.984082435

21.50952757


2016

Australia

-3.394591403

1.276990945

24190907

6.666188127

21.52658435


2017

Australia

-2.704785324

1.948647409

24601860

4.521987656

20.61296969


2018

Australia

-2.078660736

1.911400944

24982688

2.373822341

21.44074306


2019

Australia

0.575224839

1.610767873

25365745

14.05953319

21.599...
Updated on
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