A statistical program is recommended. Consider the following data for two variables, x and y. x 135 110 130 145 175 160 120 y 145 105 125 120 135 135 130 105 (a) Compute the standardized residuals for these data. (Round your answers to two decimal places.) X; Y; Standardized Residuals 135 145 110 105 130 125 145 120 175 135 160 130 120 105 Do the data include any outliers? Explain. (Round your answers to two decimal places.) The standardized residual with the largest absolute value is (b) Plot the standardized residuals against ý. Does this plot reveal any outliers? O The plot shows no possible outliers. O The plot shows one possible outlier. The plot shows two possible outliers. O The plot shows more than two possible outliers. , corresponding to y, = (c) Develop a scatter diagram for these data. Does the scatter diagram indicate any outliers in the data? O The diagram indicates that there are no possible outliers. O The diagram indicates that there is one possible outlier. O The diagram indicates that there are two possible outliers. O The diagram indicates that there are more than two possible outliers. Since this residual is ---Select--- it ---Select--- ✓an outlier.
A statistical program is recommended. Consider the following data for two variables, x and y. x 135 110 130 145 175 160 120 y 145 105 125 120 135 135 130 105 (a) Compute the standardized residuals for these data. (Round your answers to two decimal places.) X; Y; Standardized Residuals 135 145 110 105 130 125 145 120 175 135 160 130 120 105 Do the data include any outliers? Explain. (Round your answers to two decimal places.) The standardized residual with the largest absolute value is (b) Plot the standardized residuals against ý. Does this plot reveal any outliers? O The plot shows no possible outliers. O The plot shows one possible outlier. The plot shows two possible outliers. O The plot shows more than two possible outliers. , corresponding to y, = (c) Develop a scatter diagram for these data. Does the scatter diagram indicate any outliers in the data? O The diagram indicates that there are no possible outliers. O The diagram indicates that there is one possible outlier. O The diagram indicates that there are two possible outliers. O The diagram indicates that there are more than two possible outliers. Since this residual is ---Select--- it ---Select--- ✓an outlier.
Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter1: Functions
Section1.2: The Least Square Line
Problem 13E
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Transcribed Image Text:A statistical program is recommended.
Consider the following data for two variables, x and y.
X; 135 110 130 145
Y₁ 145 105 125 120 135 130 105
Xi
(a) Compute the standardized residuals for these data. (Round your answers to two decimal places.)
Y₁ Standardized Residuals
135 145
110 105
130 125
145 120
175 135
160
120
130
175
105
160 120
Do the data include any outliers? Explain. (Round your answers to two decimal places.)
The standardized residual with the largest absolute value is
(b) Plot the standardized residuals against ŷ. Does this plot reveal any outliers?
O The plot shows no possible outliers.
O The plot shows one possible outlier.
O The plot shows two possible outliers.
O The plot shows more than two possible outliers.
, corresponding to y; =
(c) Develop a scatter diagram for these data. Does the scatter diagram indicate any outliers in the data?
O The diagram indicates that there are no possible outliers.
O The diagram indicates that there is one possible outlier.
O The diagram indicates that there are two possible outliers.
O The diagram indicates that there are more than two possible outliers.
Since this residual is ---Select---
✓, it|---Select--- ✓an outlier.
Transcribed Image Text:In general, what implications does this finding have for simple linear regression?
O For simple linear regression, we can determine an outlier by looking at the scatter diagram.
O For simple linear regression, we must calculate standardized residuals, plot a standardized residual plot, and construct a scatter diagram to identify an outlier.
O For simple linear regression, it is impossible to determine whether there is an outlier using standardized residuals, a standardized residual plot, or a scatter diagram.
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