COMPONENT III
SUBJECT: BUSINESS STATISTICS
SUBMITTED BY: AADESH KHADKA(1390)
DIVISION: FY-D
SUBMITTED TO : Dr. DHIRAJ JAIN
PRN NO.- 21020621498
PROJECT REPORT
INTRODUCTION TO THE SUBJECT OF STUDY:
The study in this project is on the SHARE OF WORLD GDP OF TOP 10 COUNTRIES IN THE
YEAR 2021.
The term "Gross Domestic Product" refers to the total monetary worth of all final goods and
services produced (and sold on the market) within a country over a given time period (typically 1
year).
PURPOSE: The gross domestic product (GDP) is the most widely used indicator of economic
activity.
HISTORY: At the end of the 18th century, the first basic concept of GDP was developed. The
contemporary notion was devised by American economist Simon Kuznets in 1934 and
recognized as the primary indicator of a country's economy at the 1944 Bretton Woods
Conference.
Formula for Gross Domestic Product
The following is the formula for computing GDP using the spending approach: GDP = private
consumption + gross private investment + government investment + government spending +
(exports – imports).
OBJECTIVE: The main objective of this study is to use statistical tools while drawing
inferences from a set of given data using MS excel
Rank
Country
Share % of
world GDP
Growth %
Continent
1
United States
24.2
5.97
North America
2
China
17.8
8.02
Asia
3
Japan
5.38
2.36
Asia
4
Germany
4.46
3.05
Europe
5
United Kingdom
3.27
6.76
Europe
6
India
3.10
9.50
Asia
7
France
3.10
6.29
Europe
8
Italy
2.23
5.77
Europe
9
Canada
2.12
5.69
North America
10
South Korea
1.92
4.28
Asia
STATISTICAL TOOLS USED:
Bar diagram: A bar chart or bar graph is a chart or graph that presents categorical data with
rectangular bars with heights or lengths proportional to the values that they represent. The bars can
be plotted vertically or horizontally. The bars are all the same width, and the variable amount is
shown on one of the axes. On the other axes, the variable's measure is also shown. The heights or
lengths of the bars represent the variable's value, and these graphs can also be used to compare
two or more numbers. Bar charts can be used to illustrate frequency distribution tables, making
calculations and comprehending data easier. Vertical or horizontal bar graphs are possible. The
length or height of a bar graph is its most important attribute. If the bar graph has a longer length,
the values are greater than the data.
PIE CHART: A pie chart is a type of graph that represents the data in the circular graph. The
slices of pie show the relative size of the data. It is a type of pictorial representation of data. A pie
chart requires a list of categorical variables and the numerical variables. Here, the term “pie”
represents the whole, and the “slices” represent the parts of the whole. A pie chart is a sort of graph
that records data in a circular pattern and divides it into sectors to represent the data of a specific
component of the entire. The proportionate component of the whole is represented by each of these
sectors or slices. Pie charts, also known as pie diagrams, aid in better understanding and
representation of data. It can also be used to compare two sets of data. We all know that the pie's
total value is always 100 percent. A circle is also known to subtend a 360-degree angle. As a result,
the total of all the data equals 360°. There are two primary formulas used in pie charts based on
these: We use the formula to calculate the percentage of the provided data: 100 (Frequency x Total
Frequency). We apply the formula to convert the data into degrees: 360° (Given Data Total Value
of Data)
CORRELATION COEFFICIENTS: Correlation coefficients are used to measure how strong a
relationship is between two variables. There are several types of correlation coefficient, but the
most popular is Pearson’s. Pearson’s correlation (also called Pearson’s R) is a correlation
coefficient commonly used in linear regression. There are various forms of correlation
coefficients, but the Pearson correlation coefficient is the most prevalent (r). This metric assesses
the strength and direction of a two-variable linear relationship. It can't distinguish between
dependent and independent variables and can't represent nonlinear interactions between two
variables. A value of exactly 1.0 indicates that the two variables have a perfect positive association.
There is a positive increase in the second variable for every positive increase in the first. A score
of -1.0 indicates that the two variables have a perfect negative relationship. This demonstrates that
the variables move in opposite directions, with a positive increase in one leading to a decrease in
the other.
USE OF STATISTICAL TOOLS:
BAR DIAGRAM:
30
25
20
15
10
5
0
United States
China
Japan
Germany
United
Kingdom
India
France
Italy
Share % of world gdp
Canada
growth%
Korea
PIE CHART: SHARE %OF WORLD GDP
3%
United States
3% 3%
China
5%
4%
Japan
36%
5%
Germany
7%
United Kingdom
India
8%
France
Italy
26%
Canada
Korea
Growth %
4,28
United States
5,97
China
5,69
Japan
8,02
Germany
United
Kingdom
India
5,77
2,36
3,05
6,29
France
Italy
Canada
6,76
9,5
Korea
CORRELATION COEFFICIENT:
FORMULA-
r = 0.2383
The value of the correlation coefficient indicates two things: (i) there is a positive correlation
between Share of World GDP and GDP Growth, meaning that the direction of increase (or
decrease) of the variables is same, and (ii) there is a weak to slightly moderate correlation
between them which means the strength of association between the two variables is low and an
increase (or decrease) in one variable may cause far less increase (or decrease) in another. The
result signifies that even though both Share of World GDP and GDP Growth are positively
correlated, their relationship is poorly described by a straight line. The data points stay far from
the straight line and thus the variables have a low degree of association between them. Hence, we
can infer that as both Share of World GDP increases in any particular country, the GDP Growth
is also likely to increase but relatively at a lower proportion.
Data Interpretation and Conclusion:
1]In contrast to the correlation coefficient study at the absolute level, the strength of the
correlation here is greatly reduced as GDP Growth increases in a much smaller proportion than
increases in Share of World GDP.
2] Because there is no constant proportionate change in one variable due to another, there may be
no linear correlations between the two variables. It is possible that increasing GDP growth
further at the current state of technology will be extremely difficult, resulting in diminishing
returns to Share of World GDP.
3] The results are unreliable because the report only uses limited statistical data from 45 to 50
samples from 10 different countries. Large data sets are preferred for a thorough understanding
of the link between Share of World GDP and GDP growth..
4] Both of these variables are not independent; there are various other factors affecting Share of
World GDP besides GDP growth that must be taken into account. The most important elements
should be discovered and investigated using multivariate correlation.
When we look at the temporal trend for each country, we can see that each country has its own
portion of global GDP—each country's GDP grows every year. However, it can be seen that
countries with a higher global GDP share do not necessarily have a higher GDP growth rate in
their own country. However, the link is weak, and more research into this area is needed before
drawing any firm conclusions.
SOURCES OF DATA;
https://m.statisticstimes.com/index.php