Consider the accompanying data on x = advertising share and y = market share for a particular brand of soft drink during 10 randomly selected years. X y 0.102 0.072 0.072 0.077 0.086 0.047 0.060 0.050 0.132 0.124 0.122 0.086 0.079 0.076 0.065 (a) Construct a scatterplot for these data. y 0.11 p 0.10 0.09 0.08 y 0.11 0.10 0.09 0.08 0.070 0.052 0.059 0.051 0.039 y 0.14 p 0.12 0.10 0.00

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Consider the accompanying data on x = advertising share and y = market share for a particular brand of soft drink during 10 randomly selected years.
0.08
0.07
0.06
0.05
0.04
(a) Construct a scatterplot for these data.
y
0.11 p
0.10
0.09
O
0.12
0.14 r
0.10
0.08
0.06
X 0.102 0.072
0.04
0.072 0.077 0.086 0.047
Yes
O No
y 0.132 0.124 0.122 0.086 0.079 0.076 0.065 0.059 0.051 0.039
X
0.04 0.06 0.08 0.10 0.12 0.14
0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11
0.060 0.050
y
0.11 p
0.10
0.09
0.08
0.07
0.06
0.05
0.04
X
0.04 0.06 0.08 0.10 0.12 0.14
Ⓡ
Is the simple linear regression model appropriate for describing the relationship between x and y?
0.070 0.052
(b) Calculate the equation of the estimated regression line. (Round your numerical values to four decimal places.)
y = -0.0016 + 1.2340x
Obtain the predicted market share when the advertising share is 0.09. (Round your answer to five decimal places.)
0.1046
X
(c) Calculate the value of r². (Round your answer to four decimal places.)
0.4272
(d) Calculate a point estimate of o. (Round your answer to five decimal places.)
0.02612
x
What is the value of degrees of freedom associated with this estimate?
8
y
0.14
0.12
0.10
0.08
0.06
0.04
Interpret this value.
O This is a typical deviation of advertising share in this data set from the value predicted by the estimated regression line.
This is the percentage of the variation in market share that can be explained by the linear regression model relating market share and advertising
share.
0.04 0.05 0.06 0.07 0.08 0.09
O This is a typical deviation of market share in this data set from the value predicted by the estimated regression line.
O This is the percentage of the variation in advertising share that can be explained by the linear regression model relating market share and advertising
share.
x
0.10 0.11
Transcribed Image Text:Consider the accompanying data on x = advertising share and y = market share for a particular brand of soft drink during 10 randomly selected years. 0.08 0.07 0.06 0.05 0.04 (a) Construct a scatterplot for these data. y 0.11 p 0.10 0.09 O 0.12 0.14 r 0.10 0.08 0.06 X 0.102 0.072 0.04 0.072 0.077 0.086 0.047 Yes O No y 0.132 0.124 0.122 0.086 0.079 0.076 0.065 0.059 0.051 0.039 X 0.04 0.06 0.08 0.10 0.12 0.14 0.04 0.05 0.06 0.07 0.08 0.09 0.10 0.11 0.060 0.050 y 0.11 p 0.10 0.09 0.08 0.07 0.06 0.05 0.04 X 0.04 0.06 0.08 0.10 0.12 0.14 Ⓡ Is the simple linear regression model appropriate for describing the relationship between x and y? 0.070 0.052 (b) Calculate the equation of the estimated regression line. (Round your numerical values to four decimal places.) y = -0.0016 + 1.2340x Obtain the predicted market share when the advertising share is 0.09. (Round your answer to five decimal places.) 0.1046 X (c) Calculate the value of r². (Round your answer to four decimal places.) 0.4272 (d) Calculate a point estimate of o. (Round your answer to five decimal places.) 0.02612 x What is the value of degrees of freedom associated with this estimate? 8 y 0.14 0.12 0.10 0.08 0.06 0.04 Interpret this value. O This is a typical deviation of advertising share in this data set from the value predicted by the estimated regression line. This is the percentage of the variation in market share that can be explained by the linear regression model relating market share and advertising share. 0.04 0.05 0.06 0.07 0.08 0.09 O This is a typical deviation of market share in this data set from the value predicted by the estimated regression line. O This is the percentage of the variation in advertising share that can be explained by the linear regression model relating market share and advertising share. x 0.10 0.11
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