The data in the accompanying table represent the heights and weights of a random sample of professional baseball players. Complete the questions below. LOADING... Click the icon to view the data table. Player Height (inches) Weight (pounds) Player 1 75 223 Player 2 75 195 Player 3 72 180 Player 4 82 231 Player 5 69 185 Player 6 74 190 Player 7 75 228 Player 8 71 200 Player 9 75 230 Determine the least-squares regression line. Test whether there is a linear relation between height and weight at the α=0.05 level of significance. Determine the least-squares regression line. Choose the correct answer below. A. y=4.028x−94.1 B. y=4.028x−92.1 C. y=−92.1x+4.028 D. y=8.028x−92.1 Test whether there is a linear relation between height and weight at the α=0.05 level of significance. State the null and alternative hypotheses. Choose the correct answer below. A. H0: β1=0 H1: β1>0 B. H0: β1=0 H1: β1≠0 C. H0: β0=0 H1: β0≠0 D. H0: β0=0 H1: β0>0 Determine the P-value for this hypothesis test. P-value=nothing (Round to three decimal places as needed.) State the appropriate conclusion at the α=0.05 level of significance. Choose the correct answer below. A. Reject H0. There is sufficient evidence to conclude that a linear relation exists between the height and weight of baseball players. B. Do not reject H0. There is sufficient evidence to conclude that a linear relation exists between the height and weight of baseball players. C. Reject H0. There is not sufficient evidence to conclude that a linear relation exists between the height and weight of baseball players. D. Do not reject H0. There is not sufficient evidence to conclude that a linear relation exists between the height and weight of baseball players.
The data in the accompanying table represent the heights and weights of a random sample of professional baseball players. Complete the questions below. LOADING... Click the icon to view the data table. Player Height (inches) Weight (pounds) Player 1 75 223 Player 2 75 195 Player 3 72 180 Player 4 82 231 Player 5 69 185 Player 6 74 190 Player 7 75 228 Player 8 71 200 Player 9 75 230 Determine the least-squares regression line. Test whether there is a linear relation between height and weight at the α=0.05 level of significance. Determine the least-squares regression line. Choose the correct answer below. A. y=4.028x−94.1 B. y=4.028x−92.1 C. y=−92.1x+4.028 D. y=8.028x−92.1 Test whether there is a linear relation between height and weight at the α=0.05 level of significance. State the null and alternative hypotheses. Choose the correct answer below. A. H0: β1=0 H1: β1>0 B. H0: β1=0 H1: β1≠0 C. H0: β0=0 H1: β0≠0 D. H0: β0=0 H1: β0>0 Determine the P-value for this hypothesis test. P-value=nothing (Round to three decimal places as needed.) State the appropriate conclusion at the α=0.05 level of significance. Choose the correct answer below. A. Reject H0. There is sufficient evidence to conclude that a linear relation exists between the height and weight of baseball players. B. Do not reject H0. There is sufficient evidence to conclude that a linear relation exists between the height and weight of baseball players. C. Reject H0. There is not sufficient evidence to conclude that a linear relation exists between the height and weight of baseball players. D. Do not reject H0. There is not sufficient evidence to conclude that a linear relation exists between the height and weight of baseball players.
Chapter3: Polynomial Functions
Section3.5: Mathematical Modeling And Variation
Problem 2ECP
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Concept explainers
Correlation
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Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
Question
The data in the accompanying table represent the heights and weights of a random sample of professional baseball players. Complete the questions below.
LOADING...
|
Player
|
Height (inches)
|
Weight (pounds)
|
|
|---|---|---|---|
|
Player 1
|
75
|
223
|
|
|
Player 2
|
75
|
195
|
|
|
Player 3
|
72
|
180
|
|
|
Player 4
|
82
|
231
|
|
|
Player 5
|
69
|
185
|
|
|
Player 6
|
74
|
190
|
|
|
Player 7
|
75
|
228
|
|
|
Player 8
|
71
|
200
|
|
|
Player 9
|
75
|
230
|
Determine the least-squares regression line. Test whether there is a linear relation between height and weight at the
α=0.05
level of significance.Determine the least-squares regression line. Choose the correct answer below.
y=4.028x−94.1
y=4.028x−92.1
y=−92.1x+4.028
y=8.028x−92.1
Test whether there is a linear relation between height and weight at the
α=0.05
level of significance.State the null and alternative hypotheses. Choose the correct answer below.
H0:
β1=0
H1:
β1>0
H0:
β1=0
H1:
β1≠0
H0:
β0=0
H1:
β0≠0
H0:
β0=0
H1:
β0>0
Determine the P-value for this hypothesis test.
P-value=nothing
(Round to three decimal places as needed.)State the appropriate conclusion at the
α=0.05
level of significance. Choose the correct answer below.Reject
H0.
There is sufficient evidence to conclude that a linear relation exists between the height and weight of baseball players.Do not reject
H0.
There is sufficient evidence to conclude that a linear relation exists between the height and weight of baseball players.Reject
H0.
There is not sufficient evidence to conclude that a linear relation exists between the height and weight of baseball players.Do not reject
H0.
There is not sufficient evidence to conclude that a linear relation exists between the height and weight of baseball players.Expert Solution
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