Demographics. The average number of persons per house-hold in the United States has been shrinking steadily for as long as statistics have been kept and is approximately linear with respect to time. In 1980 there were about 2.76 persons per household, and in 2015 about 2.54 . (A) If N represents the average number of persons per house-hold and t represents the number of years since 1980 , write a linear equation that expresses N in terms of t . (B) Use this equation to estimate household size in the year 2030.
Demographics. The average number of persons per house-hold in the United States has been shrinking steadily for as long as statistics have been kept and is approximately linear with respect to time. In 1980 there were about 2.76 persons per household, and in 2015 about 2.54 . (A) If N represents the average number of persons per house-hold and t represents the number of years since 1980 , write a linear equation that expresses N in terms of t . (B) Use this equation to estimate household size in the year 2030.
Solution Summary: The author calculates the linear equation that expresses average number of persons per household N in the numbers of years since 1980.
Demographics. The average number of persons per house-hold in the United States has been shrinking steadily for as long as statistics have been kept and is approximately linear with respect to time. In
1980
there were about
2.76
persons per household, and in
2015
about
2.54
.
(A) If
N
represents the average number of persons per house-hold and
t
represents the
number of years since
1980
, write a linear equation that expresses
N
in terms of
t
.
(B) Use this equation to estimate household size in the year
2030.
Task:
Linear Algebra: Eigenvalues and Eigenvectors
Refer to Question 1 in the provided document.
Link:
https://drive.google.com/file/d/1wKSrun-GlxirS31Z9qo Hazb9tC440 AZF/view?usp=sharing
Calculus: Multivariable Optimization
r to page 2 for constrained optimization techniques.
uctions:
Analyze the function provided in the link and identify critical points using the Lagrange
multiplier method.
Discuss the importance of second-order conditions for determining maxima and minima.
Evaluate applications of multivariable optimization in real-world problems.
Link: [https://drive.google.com/file/d/1wKSrun-GlxirS31Z9qo Hazb9tC440AZF/view?usp=sharing]
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