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Broadband Lines in EU

Part 1

1.Scatter graph showing the relationship between the number of broadband lines in January 2007 and January 2011.

2.Value of correlation coefficient:

r=√R2=√0.98=0.99

3.The coefficient of determination, R2= 0.98; Regression equation: y=1.609x+15573

4.

Country

Value of x

Value of y

Actual values

Germany

14,902,200

23,993,213

26,161,950

Spain

6,652,665

10,719,711

10,892,519

UK

13,102,298

21,097,171

19,610,363

5.There is no major variation between the predicted and actual number of broadband lines in all the three countries.

Data Analysis

Description of the Data and the Source

The data used in the analysis shows the number of broadband lines in EU countries in January 2007 and January 2011. This data helps us to compare the rate of increase in uptake of broadband lines by countries in this region. The data has been obtained from Eurostat website www.appsso.eurostat.ec.europa.eu. Eurostat is located in Luxemburg, Germany and is responsible for providing high quality statistics on Europe. The organization is charged with supplying the European Union with statistics on Europe for the purpose of making inter-country and regional comparisons. The data on broadband lines in individual EU member countries enable the union to compare how different member states have invested in broadband internet connectivity and how the rate of investment in this sector is changing over time among these countries.

The Scatter Graph

The scatter graph presented above depicts the relationship between the numbers of broadband lines in individual EU countries in January 2007 and the number of these lines by January 2011. The graph is based on the assumption that the number of broadband lines in a country at present will have an impact on the number of broadband lines in the particular country in the future. The number of broadband lines in the EU member countries by January 2007 has been taken as the independent variable while the number of broadband lines in the countries by January 2011 has been considered as the dependent variable.

Correlation Coefficient and Coefficient of Determination

Correlation coefficient refers to the strength of the relationship between two variables. A correlation coefficient of +1 indicates a very strong positive relationship while a correlation coefficient of -1 indicates a very strong negative relationship. A correlation coefficient of zero, on the other hand, shows that there is no relationship between the variables being investigated. The correlation coefficient between the numbers of broadband lines in EU member countries by January 2007 and the number of the lines by January 2011 is 0.99. This shows that there is a strong positive relationship between the two sets of data. Thus, it can be concluded that the amount of a country’s investment in broadband connectivity may indicate its future investment in the sector.

The coefficient of determination indicates how well a model fits the underlying data and its values range from 0 to 1. The coefficient of determination for the data used in the above analysis is 0.98 which shows that the model fits very well to the data.

Regression Equation

The regression equation y=1.609x+15573 shows the relationship between the number of broadband lines in a country at present and the number of broadband lines expected in the country in the future. The variable x relates to the number of lines in the country at present while the variable y represents future broadband lines. The predictions made using this model for the three countries namely Germany, Spain, and the UK show that the model is valid as it does not yield major outliers.

Part 2

Trend Shown by the Series

As indicated by the four period moving averages as well as the regression line, the internet sales in the UK have been on the rise for the period between 2007 and 2011. As the graph portrays, the sales are subject to seasonal variations each year usually peaking in the last quarter. The average annual increase over the period based on the trend line is 400 million pounds.

Predictions for the Next Four Quarters

2012

£Million

Q1

1600

Q2

1700

Q3

1800

Q4

1900

Description of the Source of the Data and What is Being Measured

The source of the data on UK internet retail sales is the office of National Statistics in UK. This data shows the value of retail internet sales in the country between 2007 and 2011. The data is organized quarterly and yearly and has been measured in millions of pounds. As indicated by the data, internet retail sales in the UK have been subject to seasonal fluctuations with sales increasing over the four quarters each year. The use of moving averages and trend lines in analyzing the data helps to eliminate the effects of seasonality so that the true trend of the data can emerge. Despite the seasonal fluctuations, graphical analysis of the data shows that internet retail sales in the UK registered steady growth between 2007 and 2011 and the trend is expected to continue in the near future as indicated by the four quarters prediction.

Average Annual Increase and Average Seasonal Variations

As indicated by the trend line, the average annual increase in internet retail sales in the UK is around 400 million pounds. The seasonal variations, on the other hand, are about 62.71 million pounds. The seasonal variations of internet retail sales in the UK increase from quarter one up to quarter four.

The Values of My Predictions and their Accuracy

Extrapolation of the trend line obtained by plotting the data of internet retail sales in UK can be used to forecast the sales of the next four quarters comprising the year 2012. Extension of the trend line shows that the four quarters will register internet retail sales amounting to 1600, 1700, 1800, and 1900 million pounds, respectively. Thus, the sales are expected to grow by pound 100 million in each quarter excluding seasonal variations. The predictions are valid since they are based on the trend line of the internet retail sales data over the years 2007 to 2010. As portrayed by the data and the graph, the seasonal variations and trend of the sales have been regular to a large extent. 

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