QUESTION IMAGE
Question
the table gives the projections of the population, in millions, of a countrys residents over age 16 for selected years from 2015 to 2060. answer parts (a) through (e).
| year | population (millions) | year | population (millions) |
|---|---|---|---|
| 2020 | 266.024 | 2045 | 315.152 |
| 2025 | 276.558 | 2050 | 323.314 |
| 2030 | 286.967 | 2055 | 331.770 |
| 2035 | 297.259 | 2060 | 340.868 |
all graphs have viewing window 0, 60 by 0, 400 with xscl = 5 and yscl = 50.
the linear model is a very good fit for the data.
d. what does the model predict that the population will be in 2042?
Step1: Let \(x = 0\) represent the year 2015. Then for the year 2042, \(x=2042 - 2015=27\).
Since the linear - model is a very good fit for the data, assume the linear model is of the form \(y = mx + b\). We can use two points \((x_1,y_1)\) and \((x_2,y_2)\) from the data to find the equation of the line. Let's take \((x_1 = 0,y_1=255.161)\) (corresponding to 2015) and \((x_2 = 25,y_2 = 297.259)\) (corresponding to 2040).
First, find the slope \(m\) using the formula \(m=\frac{y_2 - y_1}{x_2 - x_1}\).
\[m=\frac{297.259 - 255.161}{25-0}=\frac{42.098}{25}=1.68392\]
Since \(y_1 = 255.161\) and \(x_1 = 0\), the \(y\) - intercept \(b = 255.161\). So the linear model is \(y=1.68392x + 255.161\).
Step2: Substitute \(x = 27\) into the linear model.
\[y=1.68392\times27+255.161\]
\[y = 45.46584+255.161\]
\[y=300.62684\]
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300.627 (rounded to three decimal places)