1. The design life of a planned municipal water-distribution system is to end in 2050, and the population in the town has been measured every 10 years since 1930 by the US Census Bureau. The reported populations are given below. Year Population 1930 25521 1940 30208 1950 30721 1960 37253 1970 38302 1980 41983 1990 56451 2000 64109 Assuming the population growth follows the logistic curve pattern, a) Perform a non-linear regression to fit the historical data to the logistic curve equation, and estimate the populations in 2050 assuming four different scenarios where the Psat is 100, 110, 120 and 130 thousand people. Also determine coefficients a and b of the logistic model for each scenario.

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1. The design life of a planned municipal water-distribution system is to end in 2050, and the
population in the town has been measured every 10 years since 1930 by the US Census Bureau.
The reported populations are given below.
Year
Population
1930
25521
1940
30208
1950
30721
1960
37253
1970
38302
1980
41983
1990
56451
2000
64109
Assuming the population growth follows the logistic curve pattern,
a) Perform a non-linear regression to fit the historical data to the logistic curve equation, and
estimate the populations in 2050 assuming four different scenarios where the Psat is 100, 110, 120
and 130 thousand people. Also determine coefficients a and b of the logistic model for each
scenario.
Transcribed Image Text:1. The design life of a planned municipal water-distribution system is to end in 2050, and the population in the town has been measured every 10 years since 1930 by the US Census Bureau. The reported populations are given below. Year Population 1930 25521 1940 30208 1950 30721 1960 37253 1970 38302 1980 41983 1990 56451 2000 64109 Assuming the population growth follows the logistic curve pattern, a) Perform a non-linear regression to fit the historical data to the logistic curve equation, and estimate the populations in 2050 assuming four different scenarios where the Psat is 100, 110, 120 and 130 thousand people. Also determine coefficients a and b of the logistic model for each scenario.
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