Question

The U.S. population in 1910 was 92 million people. In 1990, the population was 280 million. This could either be a linear or exponential model. You will create both and then look at the true population increase and decide which model is closer the the true growth.

The actual U.S. population data (in millions) was:

Which model provides a better forecast for the U.S. population for the year 2030, linear or exponential or neither?

Question 5 options:

Linear model


Exponential model


Neither

Answer 1

Answer:

The linear model means that there is a uniform increase and in this case of US population from  92  million people in  1910  to  250  million people in  1990 .  

This means an increase of  250 − 92 = 158  million in  1990 -1910 = 80  years or   158 80 = 1.975  million per year and in  x  years it will become   92 + 1.975 x  million people. This can be graphed using the linear function  1.975 ( x − 1910 ) + 92 ,

graph{1.975(x-1910)+92 [1890, 2000, 85, 260]}

The exponential model means that there is a uniform proportional increase i.e. say  p %  every year and in this case of US population from  92  million people in  1910  to  250  million people in  1990 .  

This means an increase of  250 − 92 = 158  million in  1990 − 1910 = 80  years or  

p %  given by  92 ( 1 + p ) 80 = 250  which gives us  ( 1 +p ) 80 = 250 92  which simplifies to  p = ( 250 92 ) 0.0125 − 1 = 0.0125743  or  1.25743 % .  

This can be graphed as an exponential function  92 × 1.0125743 ( x − 1910 ) , which gives population in a year  y  and this appears as graph{92(1.0125743^(x-1910)) [1900, 2000, 85, 260]}

Step-by-step explanation:

Hope this helps