Researchers initiated a long-term study of the population of American black bears. One aspect of the study was to develop a model that could be used to predict a bear's weight (since it is not practical to weigh bears in the field). One variablethought to be related to weight is the length of the bear. The accompanying data represent the lengths and weights of 12 American black bears. Complete parts (a) through (d) below.Click the icon to view the data table.Click the icon to view the critical values table.(a) Which variable is the explanatory variable based on the goals of the research?A. The weight of the bearB. The number of bearsC. The length of the bear(b) Draw a scatter diagram of the data. Choose the correct graph below.O A.В.С.D.AWeight (kg)180-A Weight (kg)180-AWeight (kg)180-ALength (cm)180-40-10040-10040-10040-100200200200200Length (cm)Length (cm)Length (cm)Weight (kg)(c) Determine the linear correlation coefficient between weight and length.The linear correlation coefficient between weight and length is r=(Round to three decimal places as needed.)(d) Does a linear relation exist between the weight of the bear and its length?The variables weight of the bear and length of the bear areassociated because r isand the absolute value of the correlation coefficient,isthan the critical value,(Round to three decimal places as needed.) Data tablecritical values for the correlation coefficientCritical Values for Correlation CoefficientTotal Length (cm)Weight (kg)138.011030.997135.06040.9500.878139.0900.811120.56070.754149.0858.0.707141.01059.0.66610 0.63211 0.60212 0.57613 0.55314 0.53215 0.51416 0.49717 0.48218 0.46819 0.45620 0.44421 0.43322 0.42323 0.41324 0.40425 0.39626 0.38827 0.38128 0.37429 0.36730 0.361141.095150.085166.0155151.5140129.5105150.0110PrintDoneThe linear correlation coefficient between weight and(Round to three decimal places as needed.)(d) Does a linear relation exist between the weight oThe variables weight of the bear and length of the b(Round to three decimal places as needed.)Click to select your answer(s).PrintDone

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Regression measures association between explanatory variable and response variable, when we use one…

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Researchers initiated a long-term study of the population of American black bears. One aspect of the study was to develop a model that could be used to predict a bear's weight (since it is not practical to weigh bears in t thought to be related to weight is the length of the bear. The accompanying data represent the lengths and weights of 12 American black bears. Complete parts (a) through (d) below. | Click the icon to view the data table. E Click the icon to view the critical values table. (a) Which variable is the explanatory variable based on the goals of the research? O A. The weight of the bear O B. The number of bears OC. The length of the bear (b) Draw a scatter diagram of the data. Choose the correct graph below. O A. OB. Oc. OD. AWeight (kg) 180- AWeight (kg) 180- Q AWeight (kg) 180- ALength (cm) 180- .... - -- .. 40+ 100 200 Length (cm) 40+ 100 200 Length (cm) 40- 100 Length (cm) 40+ 100 200 200 Weight (kg) (c) Determine the linear correlation coefficient between weight and length. The linear correlation coefficient between weight and length is r=D: (Round to three decimal places as needed.)

Researchers initiated a long-term study of the population of American black bears. One aspect of the study was to develop a model that could be used to predict a bear's weight (since it is not practical to weigh bears in t thought to be related to weight is the length of the bear. The accompanying data represent the lengths and weights of 12 American black bears. Complete parts (a) through (d) below. | Click the icon to view the data table. E Click the icon to view the critical values table. (a) Which variable is the explanatory variable based on the goals of the research? O A. The weight of the bear O B. The number of bears OC. The length of the bear (b) Draw a scatter diagram of the data. Choose the correct graph below. O A. OB. Oc. OD. AWeight (kg) 180- AWeight (kg) 180- Q AWeight (kg) 180- ALength (cm) 180- .... - -- .. 40+ 100 200 Length (cm) 40+ 100 200 Length (cm) 40- 100 Length (cm) 40+ 100 200 200 Weight (kg) (c) Determine the linear correlation coefficient between weight and length. The linear correlation coefficient between weight and length is r=D: (Round to three decimal places as needed.)

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Concept explainers

Inverse Normal Distribution

The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.

Mean, Median, Mode

It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.

Z-Scores

A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.

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Question

Researchers initiated a long-term study of the population of American black bears. One aspect of the study was to develop a model that could be used to predict a bear's weight (since it is not practical to weigh bears in the field). One variable
thought to be related to weight is the length of the bear. The accompanying data represent the lengths and weights of 12 American black bears. Complete parts (a) through (d) below.
Click the icon to view the data table.
Click the icon to view the critical values table.
(a) Which variable is the explanatory variable based on the goals of the research?
A. The weight of the bear
B. The number of bears
C. The length of the bear
(b) Draw a scatter diagram of the data. Choose the correct graph below.
O A.
В.
С.
D.
AWeight (kg)
180-
A Weight (kg)
180-
AWeight (kg)
180-
ALength (cm)
180-
40-
100
40-
100
40-
100
40-
100
200
200
200
200
Length (cm)
Length (cm)
Length (cm)
Weight (kg)
(c) Determine the linear correlation coefficient between weight and length.
The linear correlation coefficient between weight and length is r=
(Round to three decimal places as needed.)
(d) Does a linear relation exist between the weight of the bear and its length?
The variables weight of the bear and length of the bear are
associated because r is
and the absolute value of the correlation coefficient,
is
than the critical value,
(Round to three decimal places as needed.)

Data table
critical values for the correlation coefficient
Critical Values for Correlation Coefficient
Total Length (cm)
Weight (kg)
138.0
110
3
0.997
135.0
60
4
0.950
0.878
139.0
90
0.811
120.5
60
7
0.754
149.0
85
8.
0.707
141.0
105
9.
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
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
141.0
95
150.0
85
166.0
155
151.5
140
129.5
105
150.0
110
Print
Done
The linear correlation coefficient between weight and
(Round to three decimal places as needed.)
(d) Does a linear relation exist between the weight o
The variables weight of the bear and length of the b
(Round to three decimal places as needed.)
Click to select your answer(s).
Print
Done

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