RBD Assessment 1: Internet Access Trends in Great Britain (1998-2019)

This project analyzes internet access trends in Great Britain from 1998 to 2019, utilizing secondary data from the Office for National Statistics. The study employs descriptive statistics, regression analysis, and graphical representations to examine internet usage patterns on a household basis. It categorizes users by frequency (daily, weekly, monthly, and non-users) and explores the tools they use. The analysis reveals increasing internet user numbers over time, with most users accessing the internet daily, primarily via mobile devices, and the largest user age group being 16-24. Regression analysis indicates a strong positive relationship between time and different types of internet users. The study concludes that internet access is widespread, particularly among younger demographics, and provides insights into the evolving landscape of internet usage in Great Britain. The project also includes references to relevant literature, such as studies by Chadwick, Hicks, and Chatterjee.

Internet Access on
Great Britain
(1998- 2019)

Internet Access on Great Britain
(1998- 2019)
Introduction
 The study is based on internet access on Great
Britain during 1998 to 2019.
 The study takes the data from Great Britain in a
Household basis.
 The descriptive statistics, regression analysis and
graphical representation has been conducted in this
study.
 The internet uses by the users has been divided in to
various categories like daily uses, weekly uses,
monthly uses and does not uses. Moreover the study
shows the purpose or tool of the users.Sampling Method
The secondary sample observations has been selected
during 1998 to 2019.
 The study is based on secondary quantitative data and
the source of data collection is office for national
statistics.
 In study descriptive data analysis has been conducted.
In this section central tendency and dispersion are shown.
More over regression and correlation analysis has also
been conducted.
Data Interpretation
 The office for national statistics is the source of secondary
data collection.
 According to office of the national statistics Great Britain,
93% had access to the internet in 2019. Moreover Great
Britain, 93% had access to the internet in 2019 (Hicks,
Tinkler, and Allin 2013).
 The office of national statistics is the authorised UK data
statistics (Chadwick , Wesson, and Fullwood. 2013)
Graphical representation
From the figure it is clear that the number of internet users is increases in year
by year.
 Most of the users uses internet as a daily basis.
Most of the internet users uses their internet by mobile and
moreover the larger number of internet users age is 16 to24.
Analysis
It has been seen that the mean, median and mode
of internet uses during 1998 and 2019 is 62.40%,
67.5% and 90%.
The measure of dispersion that is the range,
variance and standard deviation of the internet
access is 84%, 650% and 25.49%.
Regression Analysis
 The multiple regression model is
Time= 1968.20+1.01* daily uses +0.36 * weekly uses + 0.31
* less than weekly +1.01 * did not use less than 3 month
 The correlation and coefficient of coefficient of
determination is 0.99 and 0.98, it is highly strong
and positive.
Conclusion
The study shows the number of internet user and their uses tool
in different time and age group.
 It has been concluded that most of the internet users uses their
internet on a daily basis. Moreover the most of the users age is 16
to 24.
 The regression analysis shows that there is a strong and positive
relationship between the time and types of internet users.
References and Bibliography
Chadwick, D., Wesson, C. and Fullwood, C., 2013. Internet access
by people with intellectual disabilities: Inequalities and
opportunities. Future Internet, 5(3), pp.376-397.
Chatterjee, S. and Hadi, A.S., 2015. Regression analysis by example.
John Wiley & Sons.
George, D. and Mallery, P., 2016. Descriptive statistics. In IBM SPSS
Statistics 23 Step by Step (pp. 126-134). Routledge.
Hicks, S., Tinkler, L. and Allin, P., 2013. Measuring subjective well-
being and its potential role in policy: Perspectives from the UK office
for national statistics. Social Indicators Research, 114(1), pp.73-86.