A high school administrator is interested in determining the relationship between high school students' final grades in geometry and chemistry. She randomly samples 400 students who took both classes and records their final scores (out of 100 points) and carries out a simple linear regression, using the geometry grade as the response variable and the chemistry grade as the explanatory variable, since the students take chemistry before geometry. The resulting data was used to produce the following output. Simple linear regression results: Dependent Variable: Geometry Independent Variable: Chemistry Geometry = 3.6276926 +0.91857341*Chemistry %3D Sample size: 400 R2 = 0.55808158 Estimate of error standard deviation: 9.417521 Which of the following is a reasonable interpretation of the slope of this simple linear regression? Select one: O a The slope of this regression cannot be interpreted because 0 is not in the range of chemistry scores. Ob. On average, a 1 percentage point difference in geometry score is associated with a 0.919 percentage point difference in chemistry score. O c. Getting high grades in chemistry lead students to achieve high grades in geometry. O d. On average, a 1 percentage point difference in chemistry score is associated with a 0.919 percentage point difference in geometry score.

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A high school administrator is interested in determining the relationship between high school students' final
grades in geometry and chemistry. She randomly samples 400 students who took both classes and records
their final scores (out of 100 points) and carries out a simple linear regression, using the geometry grade as
the response variable and the chemistry grade as the explanatory variable, since the students take
chemistry before geometry. The resulting data was used to produce the following output.
Simple linear regression results:
Dependent Variable: Geometry
Independent Variable: Chemistry
Geometry
= 3.6276926 + 0.91857341*Chemistry
Sample size: 400
R2
= 0.55808158
Estimate of error standard deviation: 9.417521
Which of the following is a reasonable interpretation of the slope of this simple linear regression?
Select one:
The slope of this regression cannot be interpreted because 0 is not in the range of chemistry scores.
O b. On average, a 1 percentage point difference in geometry score is associated with a 0.919
percentage point difference in chemistry score.
O c. Getting high grades in chemistry lead students to achieve high grades in geometry.
O d. On average, a 1 percentage point difference in chemistry score is associated with a 0.919
percentage point difference in geometry score.
Transcribed Image Text:A high school administrator is interested in determining the relationship between high school students' final grades in geometry and chemistry. She randomly samples 400 students who took both classes and records their final scores (out of 100 points) and carries out a simple linear regression, using the geometry grade as the response variable and the chemistry grade as the explanatory variable, since the students take chemistry before geometry. The resulting data was used to produce the following output. Simple linear regression results: Dependent Variable: Geometry Independent Variable: Chemistry Geometry = 3.6276926 + 0.91857341*Chemistry Sample size: 400 R2 = 0.55808158 Estimate of error standard deviation: 9.417521 Which of the following is a reasonable interpretation of the slope of this simple linear regression? Select one: The slope of this regression cannot be interpreted because 0 is not in the range of chemistry scores. O b. On average, a 1 percentage point difference in geometry score is associated with a 0.919 percentage point difference in chemistry score. O c. Getting high grades in chemistry lead students to achieve high grades in geometry. O d. On average, a 1 percentage point difference in chemistry score is associated with a 0.919 percentage point difference in geometry score.
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