PRECALCULUS:GRAPHICAL,...-NASTA ED.
PRECALCULUS:GRAPHICAL,...-NASTA ED.
10th Edition
ISBN: 9780134672090
Author: Demana
Publisher: PEARSON
Expert Solution & Answer
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Chapter 7.3, Problem 88E
Solution

a.

To state: A linear regression equation for the population of Anaheim if x is the number of years since 1970 and the below given table shows the population (in thousands) of Anaheim, California, and Anchorage, Alaska.

    YearAnaheim (thousand)Anchorage (thousands)
    197016648
    1980219174
    1990266226
    2000328260
    2010336292

The resultant answer is y4.49x+173.2 .

Given information:

The given table is:

    YearAnaheim (thousand)Anchorage (thousands)
    197016648
    1980219174
    1990266226
    2000328260
    2010336292

Explanation:

Consider the given table:

    YearAnaheim (thousand)Anchorage (thousands)
    197016648
    1980219174
    1990266226
    2000328260
    2010336292

Use a graphing calculator; enter the time (years) starting at x=0 for 1970 in L1, Anaheim population in L2, and Anchorage’s population in L3.

  PRECALCULUS:GRAPHICAL,...-NASTA ED., Chapter 7.3, Problem 88E , additional homework tip  1

Use LinReg feature (with L1 and L2) to obtain the linear regression model for the population of Anaheim:

  PRECALCULUS:GRAPHICAL,...-NASTA ED., Chapter 7.3, Problem 88E , additional homework tip  2PRECALCULUS:GRAPHICAL,...-NASTA ED., Chapter 7.3, Problem 88E , additional homework tip  3

Therefore, the resultant regression equation is: y4.49x+173.2

b.

To state: A linear regression equation for the population of Anchorage if x is the number of years since 1970 and the below given table shows the population (in thousands) of two fast-growing suburbs.

    YearAnaheim (thousand)Anchorage (thousands)
    197016648
    1980219174
    1990266226
    2000328260
    2010336292

The answer is y5.74x+85.2 .

Given information:

The given table is:

    YearAnaheim (thousand)Anchorage (thousands)
    197016648
    1980219174
    1990266226
    2000328260
    2010336292

Explanation:

Continue from part (a), use LinReg feature (with L1 and L3) to obtain the linear regression model for the population of Anchorage.

  PRECALCULUS:GRAPHICAL,...-NASTA ED., Chapter 7.3, Problem 88E , additional homework tip  4PRECALCULUS:GRAPHICAL,...-NASTA ED., Chapter 7.3, Problem 88E , additional homework tip  5

Therefore, the resultant linear regression equation is: y5.74x+85.2

c.

To graph: The models from part (a) and Part (b) and use these models to determine when the population of the two cities will be about the same.

Given information:

The models from part (a) and part (b) are y4.49x+173.2 and y5.74x+85.2 .

Graph:

Consider the models y4.49x+173.2 and y5.74x+85.2 .

Now enter y4.49x+173.2 and y5.74x+85.2 to graph the equations from part (a) and part (b).

And use the intersect feature to find the point of intersection:

  PRECALCULUS:GRAPHICAL,...-NASTA ED., Chapter 7.3, Problem 88E , additional homework tip  6

The x -coordinate of the point of intersection is about 70 which corresponds to the year 1970+70=2040 .

Therefore, the population of the two cities will be about the same in the year 2040.

Interpretation: Both the equations are linear equations and their intersection point is 70.4,489.296 .

Chapter 7 Solutions

PRECALCULUS:GRAPHICAL,...-NASTA ED.

Ch. 7.1 - Prob. 1ECh. 7.1 - Prob. 2ECh. 7.1 - Prob. 3ECh. 7.1 - Prob. 4ECh. 7.1 - Prob. 5ECh. 7.1 - Prob. 6ECh. 7.1 - Prob. 7ECh. 7.1 - Prob. 8ECh. 7.1 - Prob. 9ECh. 7.1 - Prob. 10ECh. 7.1 - Prob. 11ECh. 7.1 - Prob. 12ECh. 7.1 - Prob. 13ECh. 7.1 - Prob. 14ECh. 7.1 - Prob. 15ECh. 7.1 - Prob. 16ECh. 7.1 - Prob. 17ECh. 7.1 - Prob. 18ECh. 7.1 - Prob. 19ECh. 7.1 - Prob. 20ECh. 7.1 - Prob. 21ECh. 7.1 - Prob. 22ECh. 7.1 - Prob. 23ECh. 7.1 - Prob. 24ECh. 7.1 - Prob. 25ECh. 7.1 - Prob. 26ECh. 7.1 - Prob. 27ECh. 7.1 - Prob. 28ECh. 7.1 - Prob. 29ECh. 7.1 - Prob. 30ECh. 7.1 - Prob. 31ECh. 7.1 - Prob. 32ECh. 7.1 - Prob. 33ECh. 7.1 - Prob. 34ECh. 7.1 - Prob. 35ECh. 7.1 - Prob. 36ECh. 7.1 - Prob. 37ECh. 7.1 - Prob. 38ECh. 7.1 - Prob. 39ECh. 7.1 - Prob. 40ECh. 7.1 - Prob. 41ECh. 7.1 - Prob. 42ECh. 7.1 - Prob. 43ECh. 7.1 - Prob. 44ECh. 7.1 - Prob. 45ECh. 7.1 - Prob. 46ECh. 7.1 - Prob. 47ECh. 7.1 - Prob. 48ECh. 7.1 - Prob. 49ECh. 7.1 - Prob. 50ECh. 7.1 - Prob. 51ECh. 7.1 - Prob. 52ECh. 7.1 - Prob. 53ECh. 7.1 - 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Prob. 105ECh. 7.3 - Prob. 106ECh. 7.3 - Prob. 107ECh. 7.3 - Prob. 108ECh. 7.3 - Prob. 109ECh. 7.3 - Prob. 110ECh. 7.4 - Prob. 1QRCh. 7.4 - Prob. 2QRCh. 7.4 - Prob. 3QRCh. 7.4 - Prob. 4QRCh. 7.4 - Prob. 5QRCh. 7.4 - Prob. 6QRCh. 7.4 - Prob. 7QRCh. 7.4 - Prob. 8QRCh. 7.4 - Prob. 9QRCh. 7.4 - Prob. 10QRCh. 7.4 - Prob. 1ECh. 7.4 - Prob. 2ECh. 7.4 - Prob. 3ECh. 7.4 - Prob. 4ECh. 7.4 - Prob. 5ECh. 7.4 - Prob. 6ECh. 7.4 - Prob. 7ECh. 7.4 - Prob. 8ECh. 7.4 - Prob. 9ECh. 7.4 - Prob. 10ECh. 7.4 - Prob. 11ECh. 7.4 - Prob. 12ECh. 7.4 - Prob. 13ECh. 7.4 - Prob. 14ECh. 7.4 - Prob. 15ECh. 7.4 - Prob. 16ECh. 7.4 - Prob. 17ECh. 7.4 - Prob. 18ECh. 7.4 - Prob. 19ECh. 7.4 - Prob. 20ECh. 7.4 - Prob. 21ECh. 7.4 - Prob. 22ECh. 7.4 - Prob. 23ECh. 7.4 - Prob. 24ECh. 7.4 - Prob. 25ECh. 7.4 - Prob. 26ECh. 7.4 - Prob. 27ECh. 7.4 - Prob. 28ECh. 7.4 - Prob. 29ECh. 7.4 - Prob. 30ECh. 7.4 - Prob. 31ECh. 7.4 - Prob. 32ECh. 7.4 - Prob. 33ECh. 7.4 - Prob. 34ECh. 7.4 - Prob. 35ECh. 7.4 - Prob. 36ECh. 7.4 - Prob. 37ECh. 7.4 - 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