of the regression slope and inter- Age (x) SBPa (y) patients with aplastic he percentage of cytes (y). of this regression Problem 11.1? 3? Hypertension The Update to the Task Force Report on Blood Pressure O Control in Children [12] reported the observed 90th per- centile of SBP in single years of age from age 1 to 17 based on prior studies. The data for boys of average height a given in Table 11.18. are Suppose we seek a more efficient way to display the data and choose linear regression to accomplish this task. 11.13 Fit a regression line relating age to SBP, using the data in Table 11.18. TABLE 11.18 90th percentile of SBP in boys ages 1-17 of average height TABLE Period 1930-1 1935-1 1940-1 1945-1 1950-1 1955-1 1960-1 1965-1 Age (x) ? SBPa (y) Source: E 1 99 10 115 A., 141, 4 tients 2 102 11 117 3 105 12 120 4 107 13 Lymphocytes 122 5 11.19 cancer each is (per mm²) 108 14 125 6 110 15 127 1700 7 11.20 report a 111 16 130 3078 8 11.21 112 17 132 1820 9 mortali 114 2706 2086 2299 express 11.22 necess 676 2088 2013 (16), EV for 100 rable cor- a90th percentile for each 1-year age group. 11.14 Provide a 95% confidence interval for the param- eters of the regression line. 11.15 What is the predicted blood pressure for an average 13-year-old boy as estimated from the regression line? 11.16 What is the standard error of the estimate in Problem 11.15? 11.17 Answer Problems 11.15 and 11.16 for a 17-year-old boy. 11.18 Do you think the linear regression provides a good fit to the data? Why or why not? Use residual analysis to justify your answer. Cancer in Prob 11.23 an annu 11.24 rette co Hyper The INT data on women et al.) [1 quantify est
of the regression slope and inter- Age (x) SBPa (y) patients with aplastic he percentage of cytes (y). of this regression Problem 11.1? 3? Hypertension The Update to the Task Force Report on Blood Pressure O Control in Children [12] reported the observed 90th per- centile of SBP in single years of age from age 1 to 17 based on prior studies. The data for boys of average height a given in Table 11.18. are Suppose we seek a more efficient way to display the data and choose linear regression to accomplish this task. 11.13 Fit a regression line relating age to SBP, using the data in Table 11.18. TABLE 11.18 90th percentile of SBP in boys ages 1-17 of average height TABLE Period 1930-1 1935-1 1940-1 1945-1 1950-1 1955-1 1960-1 1965-1 Age (x) ? SBPa (y) Source: E 1 99 10 115 A., 141, 4 tients 2 102 11 117 3 105 12 120 4 107 13 Lymphocytes 122 5 11.19 cancer each is (per mm²) 108 14 125 6 110 15 127 1700 7 11.20 report a 111 16 130 3078 8 11.21 112 17 132 1820 9 mortali 114 2706 2086 2299 express 11.22 necess 676 2088 2013 (16), EV for 100 rable cor- a90th percentile for each 1-year age group. 11.14 Provide a 95% confidence interval for the param- eters of the regression line. 11.15 What is the predicted blood pressure for an average 13-year-old boy as estimated from the regression line? 11.16 What is the standard error of the estimate in Problem 11.15? 11.17 Answer Problems 11.15 and 11.16 for a 17-year-old boy. 11.18 Do you think the linear regression provides a good fit to the data? Why or why not? Use residual analysis to justify your answer. Cancer in Prob 11.23 an annu 11.24 rette co Hyper The INT data on women et al.) [1 quantify est
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section10.6: Summarizing Categorical Data
Problem 31PPS
Related questions
Question
Please solve using R
![of the regression
slope and inter-
Age (x)
SBPa (y)
patients with aplastic
he percentage of
cytes (y).
of this regression
Problem 11.1?
3?
Hypertension
The Update to the Task Force Report on Blood Pressure
O Control in Children [12] reported the observed 90th per-
centile of SBP in single years of age from age 1 to 17 based
on prior studies. The data for boys of average height a
given in Table 11.18.
are
Suppose we seek a more efficient way to display the data
and choose linear regression to accomplish this task.
11.13 Fit a regression line relating age to SBP, using the
data in Table 11.18.
TABLE 11.18 90th percentile of SBP in boys ages
1-17 of average height
TABLE
Period
1930-1
1935-1
1940-1
1945-1
1950-1
1955-1
1960-1
1965-1
Age (x)
?
SBPa (y)
Source: E
1
99
10
115
A., 141, 4
tients
2
102
11
117
3
105
12
120
4
107
13
Lymphocytes
122
5
11.19
cancer
each is
(per mm²)
108
14
125
6
110
15
127
1700
7
11.20
report a
111
16
130
3078
8
11.21
112
17
132
1820
9
mortali
114
2706
2086
2299
express
11.22
necess
676
2088
2013
(16),
EV for 100
rable cor-
a90th percentile for each 1-year age group.
11.14 Provide a 95% confidence interval for the param-
eters of the regression line.
11.15 What is the predicted blood pressure for an average
13-year-old boy as estimated from the regression line?
11.16 What is the standard error of the estimate in Problem
11.15?
11.17 Answer Problems 11.15 and 11.16 for a 17-year-old
boy.
11.18 Do you think the linear regression provides a good fit
to the data? Why or why not? Use residual analysis to justify
your answer.
Cancer
in Prob
11.23
an annu
11.24
rette co
Hyper
The INT
data on
women
et al.) [1
quantify
est](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fc6389447-1237-4af0-b5c6-eb1260425b55%2F1e8bc447-9f2e-464a-8dc3-e6261766d61c%2Fnnzzrdg_processed.jpeg&w=3840&q=75)
Transcribed Image Text:of the regression
slope and inter-
Age (x)
SBPa (y)
patients with aplastic
he percentage of
cytes (y).
of this regression
Problem 11.1?
3?
Hypertension
The Update to the Task Force Report on Blood Pressure
O Control in Children [12] reported the observed 90th per-
centile of SBP in single years of age from age 1 to 17 based
on prior studies. The data for boys of average height a
given in Table 11.18.
are
Suppose we seek a more efficient way to display the data
and choose linear regression to accomplish this task.
11.13 Fit a regression line relating age to SBP, using the
data in Table 11.18.
TABLE 11.18 90th percentile of SBP in boys ages
1-17 of average height
TABLE
Period
1930-1
1935-1
1940-1
1945-1
1950-1
1955-1
1960-1
1965-1
Age (x)
?
SBPa (y)
Source: E
1
99
10
115
A., 141, 4
tients
2
102
11
117
3
105
12
120
4
107
13
Lymphocytes
122
5
11.19
cancer
each is
(per mm²)
108
14
125
6
110
15
127
1700
7
11.20
report a
111
16
130
3078
8
11.21
112
17
132
1820
9
mortali
114
2706
2086
2299
express
11.22
necess
676
2088
2013
(16),
EV for 100
rable cor-
a90th percentile for each 1-year age group.
11.14 Provide a 95% confidence interval for the param-
eters of the regression line.
11.15 What is the predicted blood pressure for an average
13-year-old boy as estimated from the regression line?
11.16 What is the standard error of the estimate in Problem
11.15?
11.17 Answer Problems 11.15 and 11.16 for a 17-year-old
boy.
11.18 Do you think the linear regression provides a good fit
to the data? Why or why not? Use residual analysis to justify
your answer.
Cancer
in Prob
11.23
an annu
11.24
rette co
Hyper
The INT
data on
women
et al.) [1
quantify
est
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