Factors Affecting Internet Development

Transcription

1 Factors Affecting Internet Development 1

2 Factors Affecting Internet Development Prepared For: Dr. Abdul H. Chowdhury Business Statistics BUS 511 MBA Program, Summer 2009 Prepared By: Shahpar Sultana ID # Sabria Afrin ID # Mohaimeen Kamal ID # MBA Program School of Business North South University, Bangladesh 7 th September,

3 7 th September, 2009 Dr. Abdul H. Chowdhury Course Instructor Business Statistics BUS 511 MBA Program, School of Business North South University Subject: Submission of Project Report Dear Sir, It is our great honor to submit the report of our project report Factors Affecting Internet Development. In this endeavor, this report seeks to identify and analyze the relationships among the variables. The report contains executive summary, statistical analysis and some findings and recommendations. It would be our enormous pleasure if you find this report useful and informative to have an apparent perspective on the issue. Thanking you. Yours sincerely, Shahpar Sultana ID # Sabria Afrin ID # Mohaimeen Kamal ID #

4 Factors Affecting Internet Development A Report of Business Statistics [BUS 511] Approved by: Dr. Abdul H. Chowdhury MBA Program, School of Business North South University Prepared by: Shahpar Sultana ID # MBA Program, School of Business North South University Sabria Afrin ID # MBA Program, School of Business North South University Mohaimeen Kamal ID # MBA Program, School of Business North South University 4

5 ACKNOWLEDGEMENTS First of all we like to express our sincere gratitude to almighty Allah that we have successfully completed our report. We feel pleased to have the opportunity of expressing our heart felt and most sincere gratitude to our instructor, Prof. Dr. Abdul H. Chowdhury for his excellent guideline which mentored us the way to prepare this project report, for his constant supervision, valuable advice, continual encouragement and extraordinary patience, without which this report would have not been possible. Finally, we would like to thanks our class mates for their co operative attitude which guide us to recover the problems regarding our report. 5

6 EXECUTIVE SUMMARY Today, the Internet is increasingly making its presence felt, not only playing an important role in research and education but also serving as a catalyst to a country s socio economic, cultural and political development. It is therefore not a surprise that the Internet has become a development of the highest significance. The purpose of this study is to find out the various factors affecting the internet development, like GDP per capita, Urban Population, Literacy Rate, Telephone & Mobile user, Electricity Consumption per capita, Percentage of Educational Expenditure of GDP & Political Stability. There is a real danger that the global information society will remain global in name only if no assistance is rendered to poorer countries. While financial assistance is important to Internet growth, it may not be the sole factor that determines ICT development in a country. Therefore, it is important for us to understand what other factors may facilitate Internet development. With a better understanding of the various factors affecting Internet diffusion, it is hoped that developing countries will better target their efforts in reducing the digital divide and make the Internet a truly global information network. 6

7 Table of Content Title Acknowledgement Executive Summary Page No V Vi Chapter Origin of the report Problem Statement Need for the study Objectives of the study Flow Chart of workings 12 Chapter Introduction Energy Crisis Emerging shortages National GDP Energy and Population Energy and Poverty Energy per capita and vehicles per capita Energy per capita and Oil Consumption Population Means 18 Chapter Theoretical Model Regression Model Hypothesis Secondary Sources of Data 22 Chapter Data Descriptive Statistics Regression Test of Hypothesis Scatter Diagram 33 Chapter 5 36 Bibliography 38 7

8 List of Tables Title Page No Data 24 Descriptive Statistics 1 25 Descriptive Statistics 2 28 Model Summary 28 Correlations Statistics 31 List of Graphs Title Page No GDP vs Energy per capita 25 Unemployment rate vs Energy per capita 26 Oil Production vs Energy per capita 26 Oil consumption vs Energy per capita 27 Vehicles per capita vs Energy per capita 27 Scatter Diagram Energy per capita vs Vehicles per capita 33 Scatter Diagram Energy per capita vs Oil consumption 33 Scatter Diagram Energy per capita vs Oil production 34 Scatter Diagram Energy per capita vs Unemployment rate 34 Scatter Diagram Energy per capita vs GDP 35 8

9 Chapter 1 INTRODUCTION 9

10 1.1 Origin of the Report BUS 511 is a statistics course offered in the MBA program of NSU in order to equip students with the statistical tools. The project was initiated so that the students would get a practical exposure of statistical analysis in a project work. 1.2 Problem Statement Today, the Internet is increasingly making its presence felt, not only playing an important role in research and education but also serving as a catalyst to a country s socio economic, cultural and political development. It is therefore not a surprise that the Internet has become a development of the highest significance. Here in this paper a model is to be set up to establish the relationship between internet user rate and some related variables like GDP per capita, Urban Population, Literacy Rate, Telephone & Mobile user, Electricity Consumption per capita, Percentage of Educational Expenditure of GDP & Political Stability. The digital divide boosted by contemporary communication technologies (primarily by the Internet revolution) is fast raising concerns among nations in the developing world as it allows some individuals or nations to benefit more from the use of such technologies than others. As a result, efforts are being made by some of the poorer countries to catch up with technology by pumping resources into communication hardware and software. However, these efforts so far have not achieved much in bridging the gaps in ICT development among various countries. 10

11 1.3 Need for the study There is a real danger that the global information society will remain global in name only if no assistance is rendered to poorer countries. While financial assistance is important to Internet growth, it may not be the sole factor that determines ICT development in a country. Therefore, it is important for us to understand what other factors may facilitate Internet development. With a better understanding of the various factors affecting Internet diffusion, it is hoped that developing countries will better target their efforts in reducing the digital divide and make the Internet a truly global information network. The findings of factors affecting internet development with relationship between various factors would indicate some significant scenario how does it differ. 1.4 Objectives of the study The main objective of this research is to estimate the relationships between Rate of Internet user and some related variables like GDP per capita, Urban Population, Literacy Rate, Telephone & Mobile user, Electricity Consumption per capita, Percentage of Educational Expenditure of GDP & Political Stability. So this research is intended To find out the level of impact of GDP per capita, Urban Population, Literacy Rate, Telephone & Mobile user, Electricity Consumption per capita, Percentage of Educational Expenditure of GDP & Political Stability on Rate of Internet user. To get a practical exposure of statistical analysis including Descriptive statistics, Regression analysis, Correlation coefficient and Test of hypotheses along with level of significance in a project work. To interpret several parameter values. Policy recommendations. 11

12 1.5 Flow Chart of workings Study area Collecting data Secondary sources Journals & Reports, Web sites Data Compilation Data Processing & Analyzing Major findings corresponding with Objectives Applicable steps Final reports 12

13 Chapter 2 GENERAL BACKGROUND 13

14 2.1 Introduction The Digital Age. The Computer Age. The Information Era. These are but three names that are used to describe the current age, and they are completely accurate. Although there are still some older people that refuse to embrace the internet, most young people could not even imagine life without it. We use computers to shop, organize and print our photos, and to research all different kinds of information, among others. The discovery of the Internet technology has paved the way to a lot of major developments in life. Internet has played a very significant role in the improvements of many industries especially in the field of information technology and business development. Internet has become a common business tool used by almost all companies today. Internet has become a necessity. The need for Internet has grown very fast during the past few years. In no time, the every single household will be having its own Internet connection. 2.2 National GDP Growth in the production of goods and services is a basic determinant of how the economy fares. By allocating total production to each unit of population, the extent to which the rate of individual output contributes to the development process can be measured. It indicates the pace of per capita income growth and also the rate that resources are used up. As a single composite indicator of economic growth, it is a most powerful summary indicator of the economic state of development in its many aspects. It does not directly measure sustainable development but it is a very important measure for the economic and developmental aspects of sustainable development, including people's consumption patterns and the use of renewable resources. GDP Per Capita refers to the gross domestic product per person. GDP includes personal consumption, investments, government spending and exports that a country makes. The total values of imports are subtracted from the total. 14

15 2.3 Literacy Rate The literacy rate is the percentage of people who can read in a certain country. There are no universal definitions and standards of literacy. Unless Specified. All rates are based on the most common definition the ability to read and write at specified age. Information on Literacy, while not perfect educational result, is probably the most easily available and valid for international comparison. 2.4 Percentage of Urban Population The data used here percentage of urban population describes the percentage of the total population living in urban areas, as defined by country. 2.5 Telecommunication Structure Here the telecommunication structure is a measure of percentage of total number of telephone and mobile user, of total population. 2.6 Electricity Consumption Per Capita This is the measure of country wise how much electricity consumed in KW per capita. 2.7 Educational Expenditure Data used here as a educational expenditure represent how much the spending on educational purpose of GDP on percentage basis. 15

16 2.8 Political Stability Country wise there are many political conditions. Some countries have democracy, some have republican government, some have monarchy and some have military junta. According to our study we denote value 1 for democratic or republican government; and value 0 for monarchy and military junta. 2.9 Population Means Mean of GDP Per Capita = Mean of Urban Population(%) = Mean of Telephone & Mobile user(%) = Mean of Literacy rate(%) = Mean of Electricity Consumption per capita = 5666 KW Mean of Internet User(%) = Mean of Educational Expenditure (% of GDP) = 5.57 Mean of Political Stability =.78 16

17 Chapter 3 Statistical Approaches 17

18 3.1 Theoretical Model: Internet User =ƒ (GDP/capita, Urban Population, Telephone & Mobile user, Literacy Rate, Electricity Consumption/capita, Educational Expenditure, Political Stability) 3.2 Regression Model: A multiple regression equation was drawn as follows on the basis of Least Square Method: Ŷ = β 0 +β 1 x 1 +β 2 x 2 +β 3 x 3 +β 4 x 4 +β 5 x 5 +β 6 x 6 +β 7 x 7 Where, Ŷ = estimated percentage of internet user x 1 = GDP per capita x 2 = Urban Population x 3 = Telephone & Mobile User x 4 = Literacy rate x 5 = Electricity Consumption per capita x 6 = Educational Expenditure x 7 = Political Stability 18

19 3.3 Hypothesis H1: The higher a country s GDP per capita, the more likely that it has a higher Internet penetration. H2: The higher the literacy rate of a country s population, the higher the internet user. H3: Greater urban population tends to associate with more Internet user. H4: A well established telecommunication infrastructure in a country tends to associate with a high Internet penetration. H5: The higher the Electricity Consumption per capita of a country s, the higher percentage of the internet user. H6: Greater Education Spending of GDP (% of GDP) tends to associate with more Internet user. H7: A Stable Political Condition in a country tends to associate with a high Internet penetration. 19

20 3.4 Secondary Sources of Data Considering time and other limitations, the authors found that it would be most appropriate to work with the Central Intelligence Agency database as available in website addressed and also from a statistical website addressed Number of Observation: 50 Variables: Dependent: Internet User (% of total population of a country) Independent: GDP/Capita Literacy Rate Urban Population (% of total population of a country) Telephone & Mobile user (% of total population of a country) Electricity Consumption per Capita ( in KW) Educational Expenditure (% of GDP) Political Stability 20

21 Chapter 4 Workings 21

22 4.1 Data: Serial GDP(PPP) Per Capita, Urban Telephone & Country Internet User (%) Number ($) Population (%) Mobile User (%) 1 Australia Cuba Yemen Brunei Denmark Malaysia Sweden Norway Namibia Kenya New Zealand Finland Belgium Bolivia Jamaica Iceland Switzerland Portugal United States United Kingdom Austria Poland France Hungary Ukraine South Africa Mexico Thailand Bhutan Canada Colombia Iran Italy Zimbabwe Omen Germany Spain Hong Kong South Korea Brazil India Argentina Russia Turkey Japan Nepal Philippines Pakistan Bangladesh Indonesia

23 Serial Number Country Literacy Rate (%) Electricity Consumption/capita Education Expenditure. (% of GDP) Political Stability 1 Australia Cuba Yemen Brunei Denmark Malaysia Sweden Norway Namibia Kenya New Zealand Finland Belgium Bolivia Jamaica Iceland Switzerland Portugal United States United Kingdom Austria Poland France Hungary Ukraine South Africa Mexico Thailand Bhutan Canada Colombia Iran Italy Zimbabwe Omen Germany Spain Hong Kong South Korea Brazil India Argentina Russia Turkey Japan Nepal Philippines Pakistan Bangladesh Indonesia

24 Internet User (%) Internet User (%) Zimbabwe Bangladesh Yemen India Philippines Bolivia Bhutan Jamaica Colombia South Africa Turkey Mexico Malaysia Poland Omen South Korea France Spain United Kingdom Denmark Australia Austria Iceland Hong Kong Brunei GDP(PPP) Per Capita, ($) GDP(PPP) Per Capita, ($) 0 Zimbabwe Kenya India Indonesia Bhutan Thailand South Africa Iran Malaysia Hungary South Korea Japan United Kingdom Belgium Austria Switzerland Brunei 24

25 120 Urban Population (%) Urban Population (%) 20 0 Nepal Bangladesh Yemen Bhutan Namibia Indonesia Portugal South Africa Philippines Japan Hungary Iran Turkey Omen Russia Germany Cuba France Spain South Korea Sweden Denmark Australia Iceland Belgium 250 Telephone & Mobile User (%) Telephone & Mobile User (%) 0 Nepal Yemen Kenya Indonesia Philippines Brazil Colombia Turkey Canada Poland New Zealand Hungary Ukraine Austria Spain Iceland Germany 25

26 Literacy Rate(%) Literacy Rate(%) Bhutan Nepal Yemen Iran Namibia South Africa Turkey Brazil Colombia Zimbabwe Thailand Brunei Hong Kong Argentina South Korea Italy Sweden Belgium Switzerland United Kingdom Canada Japan Ukraine Cuba Norway Electricity Consumption(KW)/capita Electricity Consumption(KW)/capita 0 Nepal Bangladesh Pakistan Philippines Zimbabwe Thailand Iran Poland Ukraine Italy United Kingdom Denmark South Korea Japan New Zealand Sweden Norway 26

27 Education Expenditure. (% of GDP) Education Expenditure. (% of GDP) Indonesia Philippines Turkey India Hong Kong Germany Australia Thailand Colombia Mexico Poland Austria Iceland Finland Namibia Malaysia Yemen Political Stability Political Stability 0 Cuba Denmark Sweden Thailand Omen Hong Kong Yemen Kenya Finland Bolivia Iceland Portugal United Kingdom Poland Hungary South Africa Canada Iran Zimbabwe South Korea India Russia Japan Philippines Bangladesh 27

28 28

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30 30

31 31

32 4.2 Test of Hypothesis for Mean 1. GDP Per Capita Mean (x ) = 20736, Standard Deviation (S) = 16208, n = 50 H o : µ = H A : µ Test Statistic: z = x µ o / s n With α =.039 Hence Reject the Null Hypothesis H o 2. Internet User Mean (x ) = 37.47, Standard Deviation (S) = 26.29, n = 50 H o : µ = 25 H A : µ 25 Test Statistic: z = x µ o / s n With α =.001 Hence Reject the Null Hypothesis H o 32

33 3. Urban Population Mean (x ) = 66.02, Standard Deviation (S) = 20.91, n = 50 H o : µ = 50 H A : µ 50 Test Statistic: z = x µ o / s n With α =.000 Hence Reject the Null Hypothesis H o 4. Telephone & Mobile User Mean (x ) = , Standard Deviation (S) = 55.71, n = 50 H o : µ = 75 H A : µ 75 Test Statistic: z = x µ o / s n With α =.000 Hence Reject the Null Hypothesis H o 33

34 5. Literacy Rate Mean (x ) = 89.17, Standard Deviation (S) = 15.45, n = 50 H o : µ = 65 H A : µ 65 Test Statistic: z = x µ o / s n With α =.000 Hence Reject the Null Hypothesis H o 6. Electricity Consumption(KW) Per Capita Mean (x ) = 5666, Standard Deviation (S) = 6259, n = 50 H o : µ = 3000 H A : µ 3000 Test Statistic: z = x µ o / s n With α =.003 Hence Reject the Null Hypothesis H o 34

35 7. Educational Expenditure (% of GDP) Mean (x ) = 5.57, Standard Deviation (S) = 2.53, n = 50 H o : µ = 4 H A : µ 4 Test Statistic: z = x µ o / s n With α =.000 Hence Reject the Null Hypothesis H o 8. Political Stability Mean (x ) = 0.78, Standard Deviation (S) = , n = 50 H o : µ = 0 H A : µ 0 Test Statistic: z = x µ o / s n With α =.000 Hence Reject the Null Hypothesis H o 35

36 4.3 Confidence Interval For 95% Confidence Interval the range of the variables is shown in table below: Name of Variable Range Internet User (%) GDP Per Capita Urban Population (%) Telephone & Mobile User (%) Literacy Rate Electricity Consumption(KW)/capita Educational Expenditure(% of GDP) Political Stability

37 Minitab Output One-Sample Z: GDP_Per_capita Test of mu = vs not = The assumed standard deviation = Variable N Mean StDev SE Mean 95% CI Z P GDP_Per_capita (16243, 25229) One-Sample Z: Internet_User Test of mu = 25 vs not = 25 The assumed standard deviation = Variable N Mean StDev SE Mean 95% CI Z P Internet_User (30.18, 44.76) One-Sample Z: Urban_population Test of mu = 50 vs not = 50 The assumed standard deviation = Variable N Mean StDev SE Mean 95% CI Z P Urban_population (60.22, 71.82) One-Sample Z: Tel_&_Mobile_User Test of mu = 75 vs not = 75 The assumed standard deviation = Variable N Mean StDev SE Mean 95% CI Z P Tel_&_Mobile_User (93.19, ) One-Sample Z: Literacy_Rate Test of mu = 65 vs not = 65 The assumed standard deviation = Variable N Mean StDev SE Mean 95% CI Z P Literacy_Rate (84.89, 93.45)

38 One-Sample Z: Elec._Consmp_per_cap Test of mu = 3000 vs not = 3000 The assumed standard deviation = 6259 Variable N Mean StDev SE Mean 95% CI Z P Elec._Consmp_per_cap (3931, 7401) One-Sample Z: Education_Exp. Test of mu = 4 vs not = 4 The assumed standard deviation = 2.53 Variable N Mean StDev SE Mean 95% CI Z P Education_Exp (4.869, 6.271) One-Sample Z: Political_Stability Test of mu = 0 vs not = 0 The assumed standard deviation = Variable N Mean StDev SE Mean 95% CI Z Political_Stability (0.6640, ) Variable P Political_Stability

39 4.4 Descriptive Statistics Table.1: Basic Descriptive Statistics Entry Name N Minimum Maximum Mean Std. Deviation Internet User (%) GDP Per Capita ( US $) Urban Population (%) Telephone & Mobile User (%) Literacy Rate Electricity Consumption Per capita Educational Expenditure (% of GDP) Political Stability

40 Table.2: Extensive Descriptive Statistics Entry Name Internet User (%) GDP Per Capita ( US $) Urban Population (%) Telephone & Mobile User (%) Literacy Rate Electricity Consumption Per capita Educational Expenditure (% of GDP) Political Stability N Valid Missing Mean Median Mode , Stnd. Error of Mean Variance Coefficient of Variance Skewness Kurtosis Quartile Quartile

41 MINITAB OUTPUT Descriptive Statistics: Internet_Use, GDP_Per_capi, Urban_popula,... Total Variable Count N N* Mean SE Mean StDev Variance Internet_User GDP_Per_capita Urban_population Tel_&_Mobile_User Literacy_Rate Elec._Consmp_per_cap Education_Exp Political_Stability Variable CoefVar Sum of Squares Minimum Q1 Median Q3 Internet_User GDP_Per_capita Urban_population Tel_&_Mobile_User Literacy_Rate Elec._Consmp_per_cap Education_Exp Political_Stability Variable Maximum Skewness Kurtosis Internet_User GDP_Per_capita Urban_population Tel_&_Mobile_User Literacy_Rate Elec._Consmp_per_cap Education_Exp Political_Stability N for Variable Maximum Mode Mode Skewness Kurtosis Internet_User * GDP_Per_capita Urban_population , Tel_&_Mobile_User * Literacy_Rate Elec._Consmp_per_cap * Education_Exp Political_Stability

42 Internet User (%) GDP(PPP) Per Capita, Thousand($) Australia Yemen Denmark Sweden Namibia New Zealand Belgium Jamaica Switzerland United States Austria France Ukraine Mexico Bhutan Colombia Italy Omen Spain South Korea India Russia Japan Philippines Bangladesh Internet User (%) Urban Population (%) 0 42

43 Internet User (%) Literacy Rate 0 Australia Yemen Denmark Sweden Namibia New Zealand Belgium Jamaica Switzerland United States Austria France Ukraine Mexico Bhutan Colombia Italy Omen Spain South Korea India Russia Japan Philippines Bangladesh Internet User (%) Telephone & Mobile User (%) 0 Australia Brunei Sweden Kenya Belgium Iceland United States Poland Ukraine Thailand Colombia Zimbabwe Spain Brazil Russia Nepal Bangladesh 43

44 Internet User (%) Electricity Consumption(MW)/capita Australia Brunei Sweden Kenya Belgium Iceland United States Poland Ukraine Thailand Colombia Zimbabwe Spain Brazil Russia Nepal Bangladesh Internet User (%) Education Expenditure. (% of GDP) Australia Brunei Sweden Kenya Belgium Iceland United States Poland Ukraine Thailand Colombia Zimbabwe Spain Brazil Russia Nepal Bangladesh 44

45 Internet User (%) Political Stability Australia Yemen Denmark Sweden Namibia New Zealand Belgium Jamaica Switzerland United States Austria France Ukraine Mexico Bhutan Colombia Italy Omen Spain South Korea India Russia Japan Philippines Bangladesh 45

46 4.5 Regression Analysis The regression equation is Internet User = GDP Per capita Urban population Telephone & Mobile User Literacy Rate Electricity Consumption per capita Educational Expenditure Political Stability From this equation these are point out that: For a single unit change of GDP per capita, the Internet user will be changed units, and the variables share a positive relationship to each other. For a single unit change of Urban Population, the Internet user will be changed units, and the variables share a negative relationship to each other. For a single unit change of Telephone & Mobile User, the Internet user will be changed units, and the variables share a positive relationship to each other. For a single unit change of Literacy rate, the Internet user will be changed units, and the variables share a positive relationship to each other. For a single unit change of Electricity Consumption per capita, the Internet user will be changed units, and the variables share a positive relationship to each other. For a single unit change of Educational Expenditure, the Internet user will be changed units, and the variables share a positive relationship to each other. For a single unit change of Political Stability, the Internet user will be changed 2.69 units, and the variables share a positive relationship to each other. 46

47 Predictor Constant GDP Per capita Urban population Tel. & Mobile User Literacy Rate Elec. Consumption per capita Education Exp. Political Stability Coef SE Coef T P S = R Sq = 78.3% R Sq(adj) = 74.6% The coefficient of determination (R 2 ) and the adjusted value was found to be 78.3% and 74.6% respectively. That Means the Internet User can be explained 78.3% by GDP Per capita, Urban population, Telephone & Mobile User, Literacy Rate, Electricity Consumption per capita, Educational Expenditure & Political Stability. As because, we cannot except p value greater than 0.05, so; The revised regression equation is, Internet User = GDP per capita Telephone & Mobile User Electricity Consumption per capita 47

48 MINITAB OUTPUT Regression Analysis: Internet_Use versus GDP_Per_capi, Urban_popula,... The regression equation is Internet_User = GDP_Per_capita Urban_population Tel_&_Mobile_User Literacy_Rate Elec._Consmp_per_cap Education_Exp Political_Stability Predictor Coef SE Coef T P Constant GDP_Per_capita Urban_population Tel_&_Mobile_User Literacy_Rate Elec._Consmp_per_cap Education_Exp Political_Stability S = R-Sq = 78.3% R-Sq(adj) = 74.6% Analysis of Variance Source DF SS MS F P Regression Residual Error Total Source DF Seq SS GDP_Per_capita Urban_population Tel_&_Mobile_User Literacy_Rate Elec._Consmp_per_cap Education_Exp Political_Stability Unusual Observations Obs GDP_Per_capita Internet_User Fit SE Fit Residual St Resid X R R R RX R denotes an observation with a large standardized residual. X denotes an observation whose X value gives it large leverage. 48

49 4.6 Correlation Statistics Table 3: Correlation Statistics Correlation Coefficient (R) Internet User GDP Per Capita Urban Population Telephone & Mobile User Literacy Rate Electricity Consumption Per capita Educational Expenditure (% of GDP) Political Stability Internet User 1 GDP Per Capita Urban Population Telephone & Mobile User Literacy Rate Electricity Consumption Per capita Educational Expenditure (% of GDP) Political Stability

50 MINITAB OUTPUT Correlations: Internet_Use, GDP_Per_capi, Urban_popula, Tel_&_Mobile,... Internet_User GDP_Per_capita GDP_Per_capita Urban_population Urban_population Tel_&_Mobile_Use Literacy_Rate Elec._Consmp_per Education_Exp Political_Stabil Tel_&_Mobile_Use Literacy_Rate Literacy_Rate Elec._Consmp_per Elec._Consmp_per Education_Exp Political_Stabil Education_Exp. Political_Stabil

51 4.6 Scatter Plot 90 Scatterplot of Internet_User vs GDP_Per_capita Internet_User GDP_Per_capita Scatterplot of Internet_User vs Urban_population Internet_User Urban_population

52 90 Scatterplot of Internet_User vs Tel_&_Mobile_User Internet_User Tel_&_Mobile_User Scatterplot of Internet_User vs Literacy_Rate Internet_User Literacy_Rate

53 90 Scatterplot of Internet_User vs Elec._Consmp_per_cap Internet_User Elec._Consmp_per_cap Scatterplot of Internet_User vs Education_Exp Internet_User Education_Exp

54 90 Scatterplot of Internet_User vs Political_Stability Internet_User Political_Stability

55 4.7 Hypothesis Test for Correlation Hypothesis 1: The higher a country s GDP per capita, the more likely that it has a higher Internet penetration. There is a relationship between GDP per capita & Internet user. H o : ρ = 0 H A : ρ 0 Test Statistic: here, r = n = 50 α =.012 Hence Reject the Null Hypothesis H o Hence Hypothesis 1 is established. Hypothesis 2: The higher the literacy rates of a country s population, the higher the internet user. There is a relationship between literacy rates & Internet user. H o : ρ = 0 H A : ρ 0 Test Statistic: here, r = n = 50 α =.549 Hence We Fail to Reject the Null Hypothesis H o Hence Hypothesis 2 is not established. Hypothesis 3: Greater urban population tends to associate with more Internet user. There is a relationship between urban population & Internet user. H o : ρ = 0 H A : ρ 0 Test Statistic: here, r = n = 50 α =.887 Hence We Fail to Reject the Null Hypothesis H o Hence Hypothesis 3 is not established. 55

56 Hypothesis 4: A well established telecommunication infrastructure in a country tends to associate with a high Internet penetration. There is a relationship between Total Telephone and Mobile user & Internet user. H o : ρ = 0 H A : ρ 0 Test Statistic: here, r = n = 50 α =.023 Hence Reject the Null Hypothesis H o Hence Hypothesis 4 is established. Hypothesis 5: The higher the Electricity Consumption per capita of a country s, the higher percentage of the internet user. There is a relationship between Electricity Consumption per capita & Internet user. H o : ρ = 0 H A : ρ 0 Test Statistic: here, r = n = 50 α =.067 Hence Reject the Null Hypothesis H o Hence Hypothesis 5 is established. Hypothesis 6: Greater Education Spending of GDP (% of GDP) tends to associate with more Internet user. There is a relationship between Education Spending & Internet user. H o : ρ = 0 H A : ρ 0 Test Statistic: here, r = n = 50 α =.508 Hence We Fail to Reject the Null Hypothesis H o Hence Hypothesis 6 is not established. 56

57 Hypothesis 7: A Stable Political Condition in a country tends to associate with a high Internet penetration. There is a relationship between Political Condition & Internet user. H o : ρ = 0 H A : ρ 0 Test Statistic: here, r = 0.14 n = 50 α =.621 Hence We Fail to Reject the Null Hypothesis H o Hence Hypothesis 7 is not established 99 Normal Probability Plot (response is Internet_User) Percent Residual Figure: Normal Probability Plot for Residuals 57

58 Chapter 5 Findings & Recommendations 58

59 It is clear from the analysis and statistical data that GDP per capita, Literacy rate, Urban population, A well established telecommunication structure, Electricity consumption per capita all these factors have more or less have some impacts on the significance of internet user. Percentage of GDP spending on Educational purpose & Political stability don t have any significant affect on internet user rate according tour sample data of 50 countries. In the end of regression analysis, correlation & some other statistical tests we found that GDP per capita, well established telecommunication structure & electricity consumption per capita have very considerable affect on the rate of internet user in a country. The change in GDP per capita & Electricity consumption per capita is not possible in easily for developing & under developed countries. But in very low cost primary level investment of people can make the telecommunication structure very strong. As an example for our country Bangladesh there are lots of mobile operator gives us chance to get connected to internet via very cheap mobile handset. So we must recommend putting more emphasis on telecommunication structure for some rapid change on internet development for developing & under developed countries. The research was done with a number of limitations. There may be other factors apart from the other identified variables that can affect energy per capita. The research could have been better if other variables could have been studied. The research was carried out in a limited time and as a result detailed study was not possible although there were good intentions. 59

60 Bibliography 60

61 Websites: ("A Preliminary model of Internet diffusion within developing countries" by B. Bazar and G. Boalch) ( Factors affecting Internet development : An Asian survey by Hao Xiaoming and Chow Seet Kay ) 61