Data Collection And Statistical Analysis Of Global Car Sales Essay.

Objective:

This assessment task requires you to collect, analyse and interpret data with appropriate discussion and inter-pretation.

A brief description of the task:

Whilst completing this assessment task, you will identify appropriate methods of data collection relevant to your topic. You will subsequently perform the data collection and apply both qualitative and quantitative statistical analyses to draw insightful conclusions from the data. As part of this work, you are required to also identify potential sources of error in the collected data, e.g. instrumentation errors. You will also need to discuss the quality and quantity of the data that you have obtained as it relates to the topic under investigation. You will also demonstrate the use and interpretation of one- and two-dimensional statistical analysis techniques through the analysis of the collected research related datasets. Part of your work will need to include a statistical validation check and you will need to comment on the reliability and limitations using established engineering techniques. Finally, you are to also consider how to add to or improve the quality of the data to sourced – i.e. identify the sort or type of data that you will would collect and how you would go about obtaining it.

Statistics is used, here, to find a pattern within the data. Present your data and findings in the most meaningful way so that it is interesting to a professional audience. Keep in mind that this is a literature unit, as such your work will require a literature introduction and a discussion supported by literature.

You are required to write a technical report which demonstrates your ability to collect and per-form statistical analysis on data. Your report will contain original supporting graphs, tables with an insightful interpretation of the data, findings, recommendations and conclusions.

Data analysis is the method of identifying, processing and modelling a given data with the aim of getting factors that guide decision making. All businesses in the current age require data interpretation in certain instances. There has been a worldwide problem of air pollution, global warming, car accidents and congestion caused by cars. Governments and global non-governmental organizations have many times convened to come up with measures to mitigate these problems. However, the same cars which are the cause of these complications turn out to be essential in development globally, for instance the development of the car industry has led to the development of affiliate industries contributing significantly to the GDP of word nations (Patton, 1990, 72). These advancements have resulted in the employment of millions of job seekers universally. These and many more are the pros and cons of cars. The question we seek to answer is, should the manufacturing of cars be banned globally?

This project focusses on the global car industry, data has been collected on the number of car sales globally and other variables such as global warming and documented in excel. An analysis has been done between the car sales as the main variable against all the other variable. Results have been documented and a conclusion made. The results in the project show that the number of global car sales significantly affect other factors such as air pollution, global warming and job creation.

This project is documented on car sales in the world, the number of car sales is analyzed against variables such as global warming, percentage job creation, traffic congestion, air pollution, highway accidents, industries created, car related expenses and the preference of cars to big vehicles.

The project is conducted on a global scare on a period of fifty-seven (57) years from 1960 to 2017. The data used has been collected from online sources.

below:

Period (time scope)	Main Variable	Other Variables
1960-2017	Number of Cars sold in the globe in millions.	· Global Warming · Percentage Job Creation · Percentage Traffic Congestion · Percentage Air Pollution · Percentage High Way Accidents · Number of Industries Created · Percentage of Car Related Expenses   · Preference of Cars to Big Vehicles

• Effects of global car sales
• Influence of number of global car sales on Global Warming
• Influence of number of global car sales on Percentage Job Creation
• Influence of number of global car sales on Percentage Traffic Congestion
• Influence of number of global car sales on Percentage Air Pollution
• Influence of number of global car sales on Percentage High Way Accidents
• Influence of number of global car sales on Number of Industries Created
• Influence of number of global car sales on Percentage of Car Related Expenses  
• Influence of number of global car sales on Preference of Cars to Big Vehicles
• How to mitigate the effects caused by increased car sales

The report has six chapters which are arranged as follows:

Chapter 1: Introduction

Chapter 2: Literature Review

Chapter 3: Methodology

Chapter 4: Results

Chapter 5: Discussions

Chapter 6: Concluding remarks

Chapter 7: References

Additionally, there is the top page, executive summary, student contributions and table of contents at the beginning of the project and Appendices at the bottom of the project paper.

Cars are important players in the transport industry in the world today. The continued use of cars and rising number of vehicles in some nations in all continents of the world is something that is promising to the engineering sector. Moreover, it has created an avenue for the field of innovation that is promising to the world of research regarding the improvements in the development sector. Long in the memorial, horses, donkeys and street carts were the common means of transport with the improvements in the transport sector we have new brands of cars namely, Toyota, land cruiser, range rover, Vitz cut the list short. Cars are a major form of transport and are defined as a wheeled motor vehicle used for transportation (Johnson, 2003, 297-319).

Methodology

The car industry is an industry where technology is pouring in an at an unprecedented rate; incipient trends are multiplying like vehicles on the roadways at rush hour, some of the patterns are worth appreciated while others are upsetting, draining into multiple areas. The corpus usage of motor vehicles was destined to have some unanticipated and undesirable consequences, of which three cited as traffic congestion, highway accidents, and air pollutions (Gill, 2008, 291).

Anybody who purchases a car is aware of the importance of cars to the economy. Cars are on the list of expensive purchases made by a majority of the population, an auto industry that creates these cars is a vital part of any economy. An economic implication of cars is complex, but key areas where automobiles harm, or are of substantial help are a walk in the park. Creation of jobs at automakers and car dealers is one of the avenues. New plants situated in and owned by foreign automakers are sources of jobs to the inhabitants where they are erected. Transportation of new cars to merchants and merchandising them to users or customers is an additional venture for employment.

The environmental cost of cars is inseparable from economic implications. Cars contribute to 32% of total ecological air pollution added by old cars, environmental initiatives to reduce the mitigate and clean up caused by cars adopted by various states as incentives such as tax breaks aimed to compel drivers to buy more efficient fuel cars, is venture costing millions of dollars with a future to be a source of even saving more money.

The automotive industry is suffering a period of mass interference and revolution. The changing interests of consumers from ownership-centric mindset to service-centric demand that is of late blurring the industry lines and intensifying the bounds of the old-style locomotive industry. Research by world economic forum reported that digital transformation in the auto space is affecting R&DS, procurement, assembly, marketing and services, China will be the most attractive market for revenue digitalization (Jacobson, 1963, 242).

Data 

These are statistics and facts collected together for analysis or reference. Data can be categorized in to two main classes, qualitative and quantitate data.

Qualitative Data

This is data that cannot be expressed numerically but represented using other variables for example car preferences e.g. Toyota and gender.

Quantitative Data

This is data that can be expressed in numerical form. In is assumed to be more accurate compared to qualitative data. There are many formulae that are used in the analysis of numerical data in order to come up with conclusions from given data (Pfaffi, 2004, 509-515).

Results

There are a couple of steps which were involved from the project commencement to its completion as follows:

This is the first step in any data analysis project, it involves collecting data like simple polls to choose the most efficient car.

This is the process of processing data using functions and formulas, for example in excel functions such as sort and conditional formatting are applied. There is also the function of data filtering in excel that allow the user to gain insights on those values that meet certain standards (Triok, 2013, 97).  

The final computed data must be presented in order to finalize any data analysis project.  In Microsoft Excel there are a couple of charts that let the user present their data in easy ways.

The project involves comparison of various variables using Microsoft Excel. The variables’ values are entered in an excel document and various procedures are applied to aide data comparison and coming up with relevant conclusions.  The variables are as follows:

• Number of Cars Sold Globally

This is the number of cars sold in Millions in the whole world for the period between 1960-2017. The values comprise the average of all sales made from all car selling nations.

• Global Warming

This is the amount of carbon dioxide levels emitted as a result of using cars globally (Root, 2003, 97). The values are expressed in millions for the years 1960-2017.

• Percentage Job Creation

This is the percentage of jobs created globally as a result of the car production industry from the years 1960-2017. The jobs include affiliate company jobs such as insurance companies.  

• Percentage Traffic Congestion

This is the percentage of traffic created as a result of the car sales over the years 1960-2017. The percentage is calculated in comparison to the capacity of roads globally.

• Percentage Air Pollution

This is the percentage of air pollution as a result of car emissions as compared to other emissions (Pope, 2002, 101).  

• Percentage High Way Accidents

This is the percentage of car related accidents over the years in consideration of the number of cars sold globally.

• Number of Industries Created

This are the number of industries created as a result of car sales, this may range from car manufacturing companies, motor spare part companies to insurance companies.  

• Percentage of Car Related Expenses

This is the percentage of revenue spent on buying cars and other car related expenses globally compared to the total revenue.

• Preference of Cars to Big Vehicles

Microsoft Excel 

This is a software that provides functions for data analyzation that are easy to use and simple to aid the getting of meaningful conclusions from given data. The autofill button allows you to automatically fill data into the excel sheet

Discussions

The following data processing techniques are used in data analysis in Excel:

This is a type of analysis that allows the user to comprehend the relationship between two sets of data with the aim of finding a likely pattern. It facilitates the testing of whether two variables have a relationship in which one variable depends on the other. There are different correlation coefficient outcomes when analyzing data. A correlation coefficient of +1 designates a positive correlation that is perfect such that as a given variable X increases variable Y increases too while a decrease in variable X makes variable Y to decrease too. A -1 Correlation coefficient indicates a negative correlation that is perfect in nature, in this case when a given variable X increases variable Y decreases and when variable X decreases variable Y increases. The last outcome is a correlation coefficient of zero, this indicates no correlation between the two variables X and Y.

In this project the correlation formula of:

= CORREL(A2:A6,B2:B6)

Is used to find the correlation of different variables.

This is a type of analysis that determines a situation in which a change in one variable influences the value of another variable (Brauer, 2006, 107).

Covariance

This is a type of analysis that determines those variables that change together.

In this project comparison is used to compare the various parameters from the number of cars sold parameters to other variables. Inferences are made from a keen observation of the results over the period of 1960 to 2017.

In this project we apply some of these processes of Excel data analysis to aid our findings and conclusion on our data.

Since this project relies on already documented data and simulation in Microsoft excel, there is no cost on its implementation. However, there may be a purchase incurred on Microsoft excel add-ons which is subject to review.

The project Gantt chart is as shown below:

Project stage	April 27	April 28	April 29	April 30	May 1	May 2	May 3
Project Abstract
Project introduction
Literature review
Methodology
Data analysis in excel
Results
Discussions
Concluding remarks
References
Appendices
Executive Summary
Table of Contents

The project was solely executed by me, comprising all the data collection, correlations and analysis.

The table below is a pictorial representation of the excel sheet containing the data to be analyzed:

 

Table showing the various parameters and their values over a period of 57 years.

• Correlation between Number of Car sales and the Global Warming

The table below displays sample data of selected years between 1960 and 2015

Time in Years	Number of Cars sold in Millions	Global warming
1960	10,000,345	300
1965	14,900,900	309
1970	18,000,000	317
1975	20,000,000	323
1980	27,800,000	333
1985	34,300,000	345
1990	39,000,290	355
1995	39,800,000	369
2000	41,400,000	375
2005	45,000,000	383
2010	50,000,000	390
2011	50,500,000	392
2012	51,000,000	393
2013	53,000,404	395
2014	54,000,890	396
2015	72,000,610	398

By the use of comparison, it can be noted that both parameters increase gradually in most instances.

Note: Correlation is done in consideration of all years.

Concluding Remarks

The table below is a pictorial representation of the result of the correlation of the variables above:

 

The results of this correlation is 0.943516 this indicate that as the Number of Car sales increases the global warming increases and as the number of car sales decreases the global warming decreases too representing a positive correlation.

This can be attributed to the fact that an increase in the number of car sales over the years results in an increase in the emission of the waste gas carbon dioxide thus increasing the levels of global warming.

• Correlation between Number of Car sales and the Percentage Job Creation

The table below displays sample data of selected years between 1960 and 2015

Note: Correlation is done in consideration of all years.

Time in Years	Number of Cars sold in Millions	Percentage job creation
1960	10,000,345	9
1965	14,900,900	11
1970	18,000,000	12.5
1975	20,000,000	15.5
1980	27,800,000	17
1985	34,300,000	21
1990	39,000,290	24.6
1995	39,800,000	26.5
2000	41,400,000	30
2005	45,000,000	33.4
2010	50,000,000	36
2011	50,500,000	37.2
2012	51,000,000	37.7
2013	53,000,404	38
2014	54,000,890	38.7
2015	72,000,610	39

By the use of comparison, it can be noted that both parameters increase gradually in most instances.

The table below is a pictorial representation of the result of the correlation of the variables above:

 

The results of this correlation is 0.958508 this indicate that as the Number of Car sales increases the Percentage job creation increases and as the number of car sales decreases the percentage of job creation decreases too representing a positive correlation.

This outcome is so because an increase in the number of car sales leads to an increase in car manufacturing industries and affiliated industries thus creating more employment.

• Correlation between Number of Cars sold and the Percentage Traffic Congestion

The table below displays sample data of selected years between 1960 and 2015

Time in Years	Number of Cars sold in Millions	Percentage traffic congestion
1960	10,000,345	5
1965	14,900,900	7
1970	18,000,000	8.9
1975	20,000,000	10.5
1980	27,800,000	12.2
1985	34,300,000	17.1
1990	39,000,290	25
1995	39,800,000	34
2000	41,400,000	40
2005	45,000,000	47.2
2010	50,000,000	52
2011	50,500,000	52.3
2012	51,000,000	53
2013	53,000,404	54.3
2014	54,000,890	54.5
2015	72,000,610	56

By the use of comparison, it can be noted that both parameters increase gradually in most instances. 

Note: Correlation is done in consideration of all years.

The table below is a pictorial representation of the result of the correlation of the variables above:

 

The results of this correlation is 0.914014 this indicate that as the Number of Cars sold increases the Percentage traffic congestion increases and as the number of cars sold decreases the Percentage traffic congestion decreases too representing a positive correlation.

This is an obvious outcome since as there is a high car purchase there will be more cars operating on the roads thus bringing about the problem of traffic congestion. This problem is much pronounced in third world nations due to their limited resources to develop infrastructure as compared to developed nations such as the United States.

• Correlation between Number of Cars sold and the Air Pollution

The table below displays sample data of selected years between 1960 and 2015

Time in Years	Number of Cars sold in Millions	Air pollution
1960	10,000,345	20,000,000
1965	14,900,900	48,500,000
1970	18,000,000	60,000,000
1975	20,000,000	79,000,000
1980	27,800,000	94,500,000
1985	34,300,000	112,300,000
1990	39,000,290	119,000,000
1995	39,800,000	129,000,000
2000	41,400,000	140,000,000
2005	45,000,000	156,900,000
2010	50,000,000	169,700,000
2011	50,500,000	170,400,000
2012	51,000,000	175,000,000
2013	53,000,404	175,200,000
2014	54,000,890	176,400,000
2015	72,000,610	178,000,000

By the use of comparison, it can be noted that both parameters increase gradually in most instances.

References

Note: Correlation is done in consideration of all years.

The table below is a pictorial representation of the result of the correlation of the variables above:

 

The results of this correlation is 0.943185 this indicate that as the Number of Cars sold increases the Air Pollution increases and as the number of cars sold decreases the Air Pollution decreases too representing a positive correlation.

This is as a result of the emissions caused by increased use of cars due to huge car sales. This emission is impure thus causes air pollution which is considered a modern day curse.   

• Correlation between Number of Cars sold and the Percentage of Highway Accidents  

The table below displays sample data of selected years between 1960 and 2015

Note: Correlation is done in consideration of all years.

Time in Years	Number of Cars sold in Millions	Percentage high way accidents
1960	10,000,345	3
1965	14,900,900	4.5
1970	18,000,000	5.4
1975	20,000,000	7
1980	27,800,000	8
1985	34,300,000	11.5
1990	39,000,290	15
1995	39,800,000	18.4
2000	41,400,000	22
2005	45,000,000	24.2
2010	50,000,000	27.8
2011	50,500,000	28
2012	51,000,000	28.3
2013	53,000,404	28.9
2014	54,000,890	29
2015	72,000,610	29.6

By the use of comparison, it can be noted that both parameters increase gradually in most instances.

The table below is a pictorial representation of the result of the correlation of the variables above:

 

The results of this correlation is 0.934406 this indicate that as the Number of Cars sold increases the Percentage of Highway Accidents increases and as the number of cars sold decreases the Percentage of Highway Accidents decreases too representing a positive correlation.

This can be attributed to the congestion caused by high usage of cars due to a high number of car sales thus an increased level of accidents.

• Correlation between Number of Cars sold and the Number of Industries Created  

The table below displays sample data of selected years between 1960 and 2015

Note: Correlation is done in consideration of all years.

Time in Years	Number of Cars sold in Millions	Number of industries created
1960	10,000,345	45,000
1965	14,900,900	283,000
1970	18,000,000	497,000
1975	20,000,000	735,100
1980	27,800,000	890,000
1985	34,300,000	23,345,250
1990	39,000,290	48,321,000
1995	39,800,000	59,300,000
2000	41,400,000	84,900,700
2005	45,000,000	134,900,700
2010	50,000,000	169,700,000
2011	50,500,000	170,000,000
2012	51,000,000	173,342,500
2013	53,000,404	178,000,000
2014	54,000,890	180,666,000
2015	72,000,610	184,700,000

By the use of comparison, it can be noted that both parameters increase gradually in most instances.

The table below is a pictorial representation of the result of the correlation of the variables above:

 

The results of this correlation is 0.901284 this indicate that as the Number of Cars sold increases the Number of Industries Created increases and as the number of cars sold decreases the Number of Industries Created decreases too representing a positive correlation.

This is due to the fact that an increase in car sales due to an increase in demand leads to an increase in car production thus more personnel have to be employed on the car manufacturing industries besides, affiliate industries such as insurance companies and road construction companies increase and deploy more labor this it totality leads to a increased employment.

• Correlation between Number of Cars sold and the Percentage of Car Related Expenses

The table below displays sample data of selected years between 1960 and 2015

Time in Years	Number of Cars sold in Millions	Percentage of car related expenses
1960	10,000,345	4
1965	14,900,900	7.7
1970	18,000,000	10
1975	20,000,000	14
1980	27,800,000	18
1985	34,300,000	21.8
1990	39,000,290	24.9
1995	39,800,000	28
2000	41,400,000	32
2005	45,000,000	34
2010	50,000,000	38.1
2011	50,500,000	39
2012	51,000,000	39.2
2013	53,000,404	39.8
2014	54,000,890	40
2015	72,000,610	41.1

Note: Correlation is done in consideration of all years.

The table below is a pictorial representation of the result of the correlation of the variables above:

 

The results of this correlation is 0.949587 this indicate that as the Number of Cars sold increases the Percentage of Car Related Expenses increases and as the number of cars sold decreases the Percentage of Car Related Expenses decreases too representing a positive correlation.

This can be explained in that as many people buy cars they tend to assign more of their income on the purchase and maintenance of the automobiles.

• The percentage Preferences of Cars to Big Vehicles  

The table below displays sample data of selected years between 1960 and 2015

Time in Years	Preference of Cars to Big vehicles
1960	3
1965	2.5
1970	3.7
1975	4.3
1980	5
1985	5.4
1990	6.2
1995	6.5
2000	6.6
2005	6.7
2010	6.9
2011	6.9
2012	7
2013	7.1
2014	7.2
2015	8

• It is noted from the data that there is a gradual increase in the percentage Preferences of Cars to Big Vehicles over the years.

The result indicate that people prefer small cars to big Vehicles gradually in that in recent years there are more people who prefer small cars to big vehicles as compared to the past where more people opted for big vehicles to small cars. This is a dangerous trend since it will lead to increased car sales thus the problems such as air pollution and global warming associated with increased car sales will be rampant globally.

The results above indicate that there are many vices and many benefits associated with an increase in the sale of cars globally. Car manufacturing companies should check their manufacturing procedures and come up with innovative ways of producing emission free cars, this will prevent the world from experiencing high levels of air pollution and global warming. Errors in the data used in this project may be as a result of misinformation from companies, instrumentation errors such as in the measurement of air pollution and error caused by handling massive amounts of data since the data in this project is global data.

Conclusions and Recommendations 

It’s evident that the number of cars sold in the globe affect various factors both positively and negatively. In order to curb the problems of air pollution and global warming car manufacturing companies should aim at producing cars with less emissions while maintaining efficiency. Governments should encourage their citizens to use public transport means rather than everyone aiming at using their own car as evident in the statistics of preferences of cars to big vehicles this will help curb problems associated with massive car sales. Global economies should consider improving their infrastructure in order to curb highway accidents and traffic congestion. 

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