(a) If the pediatrician wants to use height to predict head circumference, determine which variable is the explanatory variable and which is the response A pediatrician wants to determine the relation that may exist between a child's height and head circumference. She randomly selects 8 children from her practice, measures their height and head circumference, and obtains the data shown in the table. Complete parts (a) through (e) to the right. variable. O The explanatory variable is head circumference and the response variable is height. Height (in.) Head Circumference (in.) 27 25.5 26 25.75 7.75 6.5 6.25 6.75 17.4 17.2 17.2 17 17.5 17.2 17.2 G The explanatory variable is height and the response variable is head circumference. (b) Draw a scatter diagram. Which of the following represents the data? OA. OB. 17.4 17.64 E Click here to see the Table of Critical Values for Correlation Coefficient. 16.9 16.9 Circ. (in) Circ. (in) OD. 17.6 28 16.9 25 16.9 Height (in) Height (in) (c) Compute the linear correlation coefficient between the height and head circumference of a child. r= 0.863 (Round to three decimal places as needed.) (d) Does a linear relation exist between height and head circumference? (Round to three decimal places as needed.) O A. Yes, the variables height and head circumference are positively associated because r is positive and the absolute value of the correlation coefficient is greater than the critical value, O B. No, the variables height and head circumference are not linearly related because r is positive and the absolute value of the correlation coefficien is less than the critical value, OC. No, the variables height and head circumference are not linearly related because r is negative and the absolute value of the correlation coefficient is less than the critical value, O D. Yes, the variables height and head circumference are positively associated because r is negative and the absolute value of the correlation coefficient is greater than the critical value, Height (in): (u) ao
(a) If the pediatrician wants to use height to predict head circumference, determine which variable is the explanatory variable and which is the response A pediatrician wants to determine the relation that may exist between a child's height and head circumference. She randomly selects 8 children from her practice, measures their height and head circumference, and obtains the data shown in the table. Complete parts (a) through (e) to the right. variable. O The explanatory variable is head circumference and the response variable is height. Height (in.) Head Circumference (in.) 27 25.5 26 25.75 7.75 6.5 6.25 6.75 17.4 17.2 17.2 17 17.5 17.2 17.2 G The explanatory variable is height and the response variable is head circumference. (b) Draw a scatter diagram. Which of the following represents the data? OA. OB. 17.4 17.64 E Click here to see the Table of Critical Values for Correlation Coefficient. 16.9 16.9 Circ. (in) Circ. (in) OD. 17.6 28 16.9 25 16.9 Height (in) Height (in) (c) Compute the linear correlation coefficient between the height and head circumference of a child. r= 0.863 (Round to three decimal places as needed.) (d) Does a linear relation exist between height and head circumference? (Round to three decimal places as needed.) O A. Yes, the variables height and head circumference are positively associated because r is positive and the absolute value of the correlation coefficient is greater than the critical value, O B. No, the variables height and head circumference are not linearly related because r is positive and the absolute value of the correlation coefficien is less than the critical value, OC. No, the variables height and head circumference are not linearly related because r is negative and the absolute value of the correlation coefficient is less than the critical value, O D. Yes, the variables height and head circumference are positively associated because r is negative and the absolute value of the correlation coefficient is greater than the critical value, Height (in): (u) ao
MATLAB: An Introduction with Applications
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Author:Amos Gilat
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Contingency Table
A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.
Binomial Distribution
Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.
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Question
Solve question (d) please
![A pediatrician wants to determine the relation that may exist between a child's
height and head circumference. She randomly selects 8 children from her
practice, measures their height and head circumference, and obtains the data
shown in the table. Complete parts (a) through (e) to the right.
(a) If the pediatrician wants to use height to predict head circumference,
determine which variable is the explanatory variable and which is the response
variable,
Height (in.) Head Circumference (in.)
17.4
17.2
O The explanatory variable is head circumference and the response variable
is height.
27
25.5
26
25.75
27.75
26.5
26.25
26.75
The explanatory variable is height and the response variable is head
circumference.
17.2
17
17.5
(b) Draw a scatter diagram. Which of the following represents the data?
17.2
OA.
OB.
17.2
17.4
28
17.6
Click here to see the Table of Critical Values for Correlation Coefficient.
16.9-
16.9
17.6
Circ. (in)
Circ. (in)
OD.
17.64
28-
16.94
25
Height (in)
169
Height (in)
(c) Compute the linear correlation coefficient between the height and head
circumference of a child.
r= 0.863
(Round to three decimal places as needed.)
(d) Does a linear relation exist between height and head circumference?
(Round to three decimal places as needed.)
O A. Yes, the variables height and head circumference are positively
associated because r is positive and the absolute value of the
correlation coefficient is greater than the critical value,
O B. No, the variables height and head circumference are not linearly related
because r is positive and the absolute value of the correlation coefficient
is less than the critical value,
O C. No, the variables height and head circumference are not linearly related
because r is negative and the absolute value of the correlation
coefficient is less than the critical value,
O D. Yes, the variables height and head circumference are positively
associated because r is negative and the absolute value of the
correlation coefficient is greater than the critical value,
(u) jybia
(u) aybiaH](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F8946d1df-c200-444b-8e64-cf2805c3cc7b%2Fd1d8414d-83f4-4f7a-8da5-8362c502ce88%2Fzkd42cp_processed.jpeg&w=3840&q=75)
Transcribed Image Text:A pediatrician wants to determine the relation that may exist between a child's
height and head circumference. She randomly selects 8 children from her
practice, measures their height and head circumference, and obtains the data
shown in the table. Complete parts (a) through (e) to the right.
(a) If the pediatrician wants to use height to predict head circumference,
determine which variable is the explanatory variable and which is the response
variable,
Height (in.) Head Circumference (in.)
17.4
17.2
O The explanatory variable is head circumference and the response variable
is height.
27
25.5
26
25.75
27.75
26.5
26.25
26.75
The explanatory variable is height and the response variable is head
circumference.
17.2
17
17.5
(b) Draw a scatter diagram. Which of the following represents the data?
17.2
OA.
OB.
17.2
17.4
28
17.6
Click here to see the Table of Critical Values for Correlation Coefficient.
16.9-
16.9
17.6
Circ. (in)
Circ. (in)
OD.
17.64
28-
16.94
25
Height (in)
169
Height (in)
(c) Compute the linear correlation coefficient between the height and head
circumference of a child.
r= 0.863
(Round to three decimal places as needed.)
(d) Does a linear relation exist between height and head circumference?
(Round to three decimal places as needed.)
O A. Yes, the variables height and head circumference are positively
associated because r is positive and the absolute value of the
correlation coefficient is greater than the critical value,
O B. No, the variables height and head circumference are not linearly related
because r is positive and the absolute value of the correlation coefficient
is less than the critical value,
O C. No, the variables height and head circumference are not linearly related
because r is negative and the absolute value of the correlation
coefficient is less than the critical value,
O D. Yes, the variables height and head circumference are positively
associated because r is negative and the absolute value of the
correlation coefficient is greater than the critical value,
(u) jybia
(u) aybiaH
![Critical Values for Correlation Coefficient
3.
0.997
4 0.950
0.878
0.811
0.754
0.707
0.666
10 |0.632
11 0.602
12 0.576
13 0.553
14 0.532
15 0.514
16 0.497
17 0.482
18 0.468
19 0.456
9.
8.
9.
20 0.444
21 0.433
22 0.423
23 0.413
24 0.404
25 0.396
26 0.388
27 0.381
28 0.374
29 0.367
30 0.361](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F8946d1df-c200-444b-8e64-cf2805c3cc7b%2Fd1d8414d-83f4-4f7a-8da5-8362c502ce88%2F4pfpzj_processed.jpeg&w=3840&q=75)
Transcribed Image Text:Critical Values for Correlation Coefficient
3.
0.997
4 0.950
0.878
0.811
0.754
0.707
0.666
10 |0.632
11 0.602
12 0.576
13 0.553
14 0.532
15 0.514
16 0.497
17 0.482
18 0.468
19 0.456
9.
8.
9.
20 0.444
21 0.433
22 0.423
23 0.413
24 0.404
25 0.396
26 0.388
27 0.381
28 0.374
29 0.367
30 0.361
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