Question
Function f represents the population , in millions , of Franklin x years from now. Function g represents the population , in millions , of Georgetown x years from now, If the pattern shown in the table continue , will franklin always have a greater population than Georgetown ? Explain.
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)
Hint:
1. When the difference between 2 consecutive output values (y values) for a given constant change in the input values (x values) is constant. i.e. y(n)- y(n-1) is constant for any value of n, the function is known as a linear function.
2. When the difference between 2 consecutive differences for output values (y values) for a given constant change in the input values (x values) is constant. i.e. dy(n)- dy(n-1) is constant for any value of n, the function is known as a quadratic function.
3. When the ratio between 2 consecutive output values (y values) for a given constant change in the input values (x values) is constant i.e. y(n)/y(n-1) is constant for any value of n, the function is known as an exponential function.
The correct answer is: Since the population of Franklin is a Linear function and that of Georgetown is an exponential function, Franklin will not have a greater population in the long run.
Step-by-step solution:-
From the given table, we observe the following readings-
x1 = 0, y1(f) = 3.4, y1(g) = 2.4;
x2 = 1, y2(f) = 5.6, y1(g) = 3.6;
x3 = 2, y3(f) = 7.8, y1(g) = 5.4;
x4 = 3, y4(f) = 10, y1(g) = 8.1
Difference between 2 consecutive x values-
dx1 = x2 - x1 = 1 - 0 = 1
dx2 = x3 - x2 = 2 - 1 = 1
dx3 = x4 - x3 = 3 - 2 = 1
a). For Franklin-
Difference between 2 consecutive y values-
dy1 = y2 - y1 = 5.6 - 3.4 = 2.2
dy2 = y3 - y2 = 7.8 - 5.6 = 2.2
dy3 = y4 - y3 = 10 - 7.8 = 2.2
We observe that the difference for every consecutive x values is constant i.e. 1 and for y values the difference is constant i.e. 2.2.
Hence, the given function is a linear function.
b). For Georgetown-
Difference between 2 consecutive y values-
dy1 = y2 - y1 = 3.6 - 2.4 = 1.2
dy2 = y3 - y2 = 5.4 - 3.6 = 1.8
dy3 = y4 - y3 = 8.1 - 5.4 = 2.7
We observe that the difference for every consecutive x values is constant i.e. 1 but for y values the difference is not constant.
Hence, the given function is not a linear function.
Now, ratio between 2 consecutive y values-
= 3.6/2.4 = 1.5
= 5.4/3.6 = 1.5
= 8.1/5.4 = 1.5
We observe that difference between 2 consecutive y values is constant i.e. 1.5.
Hence, the given function is an exponential function.
We know from the above calculations that the population growth of Franklin is a Linear function and that of Georgetown is an exponential function. We also know that for a linear function, the rate of change in output for a given change in input is linear i.e. constant. However, for an exponential function, the rate of change in output for a given change in input keeps increasing at an exponential level. Hence, the population of Georgetown will far exceed that of Franklin in the long run.
Final Answer:-
∴ Since the population of Franklin is a Linear function and that of Georgetown is an exponential function, Franklin will not have a greater population in the long run.
x2 = 1, y2(f) = 5.6, y1(g) = 3.6;
x3 = 2, y3(f) = 7.8, y1(g) = 5.4;
x4 = 3, y4(f) = 10, y1(g) = 8.1
Difference between 2 consecutive x values-
dx1 = x2 - x1 = 1 - 0 = 1
dx2 = x3 - x2 = 2 - 1 = 1
dx3 = x4 - x3 = 3 - 2 = 1
a). For Franklin-
Difference between 2 consecutive y values-
dy1 = y2 - y1 = 5.6 - 3.4 = 2.2
dy2 = y3 - y2 = 7.8 - 5.6 = 2.2
dy3 = y4 - y3 = 10 - 7.8 = 2.2
We observe that the difference for every consecutive x values is constant i.e. 1 and for y values the difference is constant i.e. 2.2.
Hence, the given function is a linear function.
b). For Georgetown-
Difference between 2 consecutive y values-
dy1 = y2 - y1 = 3.6 - 2.4 = 1.2
dy2 = y3 - y2 = 5.4 - 3.6 = 1.8
dy3 = y4 - y3 = 8.1 - 5.4 = 2.7
We observe that the difference for every consecutive x values is constant i.e. 1 but for y values the difference is not constant.
Hence, the given function is not a linear function.
Now, ratio between 2 consecutive y values-
We observe that difference between 2 consecutive y values is constant i.e. 1.5.
Hence, the given function is an exponential function.
We know from the above calculations that the population growth of Franklin is a Linear function and that of Georgetown is an exponential function. We also know that for a linear function, the rate of change in output for a given change in input is linear i.e. constant. However, for an exponential function, the rate of change in output for a given change in input keeps increasing at an exponential level. Hence, the population of Georgetown will far exceed that of Franklin in the long run.
Final Answer:-
∴ Since the population of Franklin is a Linear function and that of Georgetown is an exponential function, Franklin will not have a greater population in the long run.