The populations P (in thousands) of a particular county from 1980 through 2010 can be modeled by P = 22.1 + 80.7e0.0320t where t represents the year, with t= 0 corresponding to 1980. (a) Use the model to complete the table. (Round your answers to two decimal places.) Year 1980 1990 2000 2010 Population P (in thousands) 102.8 175.1 232.8 312.3 (b) According to the model, in what year will the population of the county reach 330,000? | 4088.94 (c) Do you think the model is valid for long-term predictions of the population? Explain. O Yes, the population doesn't grow or shrink. No, the population will not continue to grow at this quick rate. Yes, the population will not continue to grow at this quick rate. Yes, the population will continue to grow at this quick rate. No, the population will continue to grow at this quick rate.

The populations P (in thousands) of a particular county from 1980 through 2010 can be modeled by P = 22.1 + 80.7e0.0320t where t represents the year, with t= 0 corresponding to 1980. (a) Use the model to complete the table. (Round your answers to two decimal places.) Year 1980 1990 2000 2010 Population P (in thousands) 102.8 175.1 232.8 312.3 (b) According to the model, in what year will the population of the county reach 330,000? | 4088.94 (c) Do you think the model is valid for long-term predictions of the population? Explain. O Yes, the population doesn't grow or shrink. No, the population will not continue to grow at this quick rate. Yes, the population will not continue to grow at this quick rate. Yes, the population will continue to grow at this quick rate. No, the population will continue to grow at this quick rate.

Calculus: Early Transcendentals

8th Edition

ISBN:9781285741550

Author:James Stewart

Publisher:James Stewart

Chapter1: Functions And Models

Section: Chapter Questions

Problem 1RCC: (a) What is a function? What are its domain and range? (b) What is the graph of a function? (c) How...

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Concept explainers

Continuous Probability Distributions

Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.

Normal Distribution

Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!

Question

The populations P (in thousands) of a particular county from 1980 through 2010 can be modeled by
P = 22.1 + 80.7e0.0320t
where t represents the year, with t = 0 corresponding to 1980.
(a) Use the model to complete the table. (Round your answers to two decimal places.)
Year
1980
1990
2000
2010
Population P (in thousands)
102.8
175.1
232.8
312.3
(b) According to the model, in what year will the population of the county reach 330,000?
4088.94
(c) Do you think the model is valid for long-term predictions of the population? Explain.
O Yes, the population doesn't grow or shrink.
No, the population will not continue to grow at this quick rate.
Yes, the population will not continue to grow at this quick rate.
Yes, the population will continue to grow at this quick rate.
No, the population will continue to grow at this quick rate.
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