Question

The data below shows age (*x*, in years) and weekly
entertainment expenses (*y*, in dollars) for a random sample
of ten adults. The least squares regression model for this data is
yˆ=344.07 − 4.21x.y^=344.07 − 4.21x. Select all valid statements
regarding the use of this regression model.

**You must make a selection for each option. Click once to
place a check mark for correct answers and click twice to place an
"x" for the wrong answers.**

- It is appropriate to use this model to predict average weekly entertainment expenses for a 53-year-old adult.unanswered
- It is appropriate to use this model to predict average weekly entertainment expenses for a 36-year-old adult.unanswered
- It is appropriate to use this model to predict average weekly entertainment expenses for a 19-year-old adult.unanswered
- It is appropriate to use this model to predict average weekly entertainment expenses for a 65-year-old adult.unanswered

Age | Entertainment expenses |

21 | 242 |

23 | 265 |

27 | 275 |

30 | 192 |

33 | 215 |

42 | 98 |

45 | 164 |

47 | 128 |

55 | 159 |

61 | 85 |

Answer #1

y^=344.07 − 4.21x

as the model contain the values of 53 and 36 but not 19 and 65.

- It is appropriate to use this model to predict average weekly entertainment expenses for a 53-year-old adult. True
- It is appropriate to use this model to predict average weekly entertainment expenses for a 36-year-old adult. True
- It is appropriate to use this model to predict average weekly entertainment expenses for a 19-year-old adult. False
- It is appropriate to use this model to predict average weekly entertainment expenses for a 65-year-old adult. False

Following are age and price data for 8 randomly selected
ambulances between 1 and 6 years old. Here, x denotes age, in
years, and y denotes price, in hundreds of dollars. Use the
information to complete parts (a) through (f).
x 6 1 6 2 6 2 4 5
y 280 390 245 350 275 370 335 300
a. Find the regression equation for the data points.
y with caret = _____+ ________ x (Round to two...

Data was gathered on 29 people to investigate the relationship
between age (x) and Systolic Blood Pressure (y). The scatter plot
and Summary Statistics are shown below. a) Use the scatterplot and
Summary Statistics to describe the direction and strength of the
relationship between Age and Systolic Blood Pressure, referencing
the appropriate statistic. b) What is the regression
equation for predicting Systolic Blood Pressure from Age?
c) What are the Null and Alternate hypotheses for testing whether
there is a...

In exercise 12, the following data on x = average daily
hotel room rate and y = amount spent on entertainment
(The Wall Street Journal, August 18, 2011) lead to the
estimated regression equation ŷ = 17.49 + 1.0334x. For
these data SSE = 1541.4.
Click on the datafile logo to reference the data. Use Table 1 of
Appendix B.
City
Room Rate ($)
Entertainment ($)
Boston
148
161
Denver
96
105
Nashville
91
101
New
Orleans
110
142
Phoenix...

The accompanying table shows a portion of data consisting of the
selling price, the age, and the mileage for 20 used sedans.
Selling Price
Age
Miles
13,604
7
61,459
13,831
7
54,341
⋮
⋮
⋮
11,951
9
42,432
a. Determine the sample regression equation
that enables us to predict the price of a sedan on the basis of its
age and mileage. (Negative values should be indicated by a
minus sign. Round your answers to 2 decimal places.) [If you...

Data was gathered on 29 people to
investigate the relationship between age (x) and Systolic Blood
Pressure (y). The scatter plot and Summary Statistics are shown
below.
Use the scatterplot and Summary Statistics to describe the
direction and strength of the relationship between Age and Systolic
Blood Pressure, referencing the appropriate statistic.
The graph is positive linear as it is
going upwards where it also provides a correlation of 0.844 this
shows a strong relationship between age and systolic pressure...

Avg Outside Temp
Attic Insulation (inches)
Age of Furnace (years)
Square Footage
Avg Heating Cost
29
5
4
1900
198
8
6
7
2800
355
6
10
9
2500
291
22
8
11
2000
230
55
2
4
1300
121
36
2
5
2100
250
28
4
9
2400
360
36
7
2
2300
164
59
5
9
1300
42
64
5
6
1500
90
19
4
8
2300
271
57
5
3
1400
96
39
7
11
1900
187...

Let x be the age in years of a licensed automobile
driver. Let y be the percentage of all fatal accidents
(for a given age) due to speeding. For example, the first data pair
indicates that 34% of all fatal accidents of 17-year-olds are due
to speeding.
Given: Σx = 329, Σy = 114,
Σx2 = 18,263,
Σy2 = 2582, Σxy =
3988, and r ≈ −0.961.
(c) Find x, and y. Then find the equation of
the least-squares line...

19. The accompanying table shows a portion of data consisting of
the selling price, the age, and the mileage for 20 used sedans.
Selling Price
Age
Miles
13,632
6
61,524
13,750
4
54,396
⋮
⋮
⋮
11,968
8
42,398
a. Determine the sample regression equation that
enables us to predict the price of a sedan on the basis of its age
and mileage. (Negative values should be indicated by a
minus sign. Round your answers to 2 decimal places.) [If...

Let x be the age of a licensed driver in years. Let
y be the percentage of all fatal accidents (for a given
age) due to failure to yield the right of way. For example, the
first data pair states that 5% of all fatal accidents of
37-year-olds are due to failure to yield the right of way.
x
37
47
57
67
77
87
y
5
8
10
15
31
44
Complete parts (a) through (e), given Σx =...

Let x be the age of a licensed driver in years. Let
y be the percentage of all fatal accidents (for a given
age) due to failure to yield the right of way. For example, the
first data pair states that 5% of all fatal accidents of
37-year-olds are due to failure to yield the right of way.
x
37
47
57
67
77
87
y
5
8
10
14
33
44
Complete parts (a) through (e), given Σx =...

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