# Question: Mobile phones as cellular phones are often called outside the

Mobile phones (as cellular phones are often called outside the United States) have replaced traditional landlines in parts of the developing world where it has been impractical to build the infrastructure needed for landlines. These data from the ITU (International Telecommunication Union) estimate the number of mobile and landline subscribers (in thousands) in Sub-Saharan Africa outside of South Africa. The data are annual, from 1995 through 2010.

(a) On the same axes, show timeplots of the two types of subscribers versus year. Does either curve appear linear?

(b) Create a scatterplot for the number of landline subscribers on the year of the count and then ft a linear equation with the number of subscribers as the response and the year as the explanatory variable. Does the r2 of this fitted equation mean that it’s a good summary?

(c) What do the slope and intercept tell you, if you accept this equation’s description of the pattern in the data?

(d) Do the residuals from the linear equation confirm your impression of the ft of the model?

(e) Does a curve of the form

Estimated loge (Number of Subscribers) = b0 + b1 Year

provide a better summary of the growth of the use of landlines? Use the residuals to help you decide.

(f) Fit a similar logarithmic equation to the growth in the number of mobile phone users. The curve is not such a nice fit, but allows some comparison to the growth in the number of land lines. How do the approximate rates of growth compare?

(a) On the same axes, show timeplots of the two types of subscribers versus year. Does either curve appear linear?

(b) Create a scatterplot for the number of landline subscribers on the year of the count and then ft a linear equation with the number of subscribers as the response and the year as the explanatory variable. Does the r2 of this fitted equation mean that it’s a good summary?

(c) What do the slope and intercept tell you, if you accept this equation’s description of the pattern in the data?

(d) Do the residuals from the linear equation confirm your impression of the ft of the model?

(e) Does a curve of the form

Estimated loge (Number of Subscribers) = b0 + b1 Year

provide a better summary of the growth of the use of landlines? Use the residuals to help you decide.

(f) Fit a similar logarithmic equation to the growth in the number of mobile phone users. The curve is not such a nice fit, but allows some comparison to the growth in the number of land lines. How do the approximate rates of growth compare?

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