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• Example 1: A group of teachers is interested in knowing whether a relationship exists between the average number of hours studied per week and high school cumulative grade point average (G.P.A.). The teachers obtain a random sample of students and determine the average number of hours each student studies along with the student's cumulative high school G.P.A. Construct a 95% confidence interval for the true slope of the regression line to help answer the teachers' question. Figure 10.1 presents a data table containing the average number of hours studied per week and the corresponding G.P.A for the 20 high-school students in the sample, along with a scatterplot of the data. GPA 2 1 0 Scatter Plot 000 0 2 4 6 8 10 12 Ave_Hrs 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Ave Hrs 10.5 3.0 6.5 8.0 8.5 2.5 9.5 1.0 4.6 3.5 2.2 6.0 8.0 6.0 5.0 3.0 5.0 4.0 9.0 7.0 GPA 4.571 2.800 3.888 4.055 3.920 3.134 4.445 1.777 2.770 3.112 2.308 3.665 4.500 3.333 3.100 2.723 3.888 3.500 4.334 3.388 Figure 10.1 A scatterplot of the data appears roughly linear with no apparent outliers.

• Example 1: A group of teachers is interested in knowing whether a relationship exists between the average number of hours studied per week and high school cumulative grade point average (G.P.A.). The teachers obtain a random sample of students and determine the average number of hours each student studies along with the student's cumulative high school G.P.A. Construct a 95% confidence interval for the true slope of the regression line to help answer the teachers' question. Figure 10.1 presents a data table containing the average number of hours studied per week and the corresponding G.P.A for the 20 high-school students in the sample, along with a scatterplot of the data. GPA 2 1 0 Scatter Plot 000 0 2 4 6 8 10 12 Ave_Hrs 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Ave Hrs 10.5 3.0 6.5 8.0 8.5 2.5 9.5 1.0 4.6 3.5 2.2 6.0 8.0 6.0 5.0 3.0 5.0 4.0 9.0 7.0 GPA 4.571 2.800 3.888 4.055 3.920 3.134 4.445 1.777 2.770 3.112 2.308 3.665 4.500 3.333 3.100 2.723 3.888 3.500 4.334 3.388 Figure 10.1 A scatterplot of the data appears roughly linear with no apparent outliers.

College Algebra
College Algebra
7th Edition
ISBN:9781305115545
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:James Stewart, Lothar Redlin, Saleem Watson
Chapter1: Equations And Graphs
Section: Chapter Questions
Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...
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• Example 1: A group of teachers is interested in knowing whether a relationship exists between the average number of hours studied per week and high school cumulative grade point average (G.P.A.). The teachers obtain a random sample of students and determine the average number of hours each student studies along with the student's cumulative high school G.P.A. Construct a 95% confidence interval for the true slope of the regression line to help answer the teachers' question. Figure 10.1 presents a data table containing the average number of hours studied per week and the corresponding G.P.A for the 20 high-school students in the sample, along with a scatterplot of the data. GPA 2 1 0 Scatter Plot 000 0 2 4 6 8 10 12 Ave_Hrs 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Ave Hrs 10.5 3.0 6.5 8.0 8.5 2.5 9.5 1.0 4.6 3.5 2.2 6.0 8.0 6.0 5.0 3.0 5.0 4.0 9.0 7.0 GPA 4.571 2.800 3.888 4.055 3.920 3.134 4.445 1.777 2.770 3.112 2.308 3.665 4.500 3.333 3.100 2.723 3.888 3.500 4.334 3.388 Figure 10.1 A scatterplot of the data appears roughly linear with no apparent outliers.
Transcribed Image Text:• Example 1: A group of teachers is interested in knowing whether a relationship exists between the average number of hours studied per week and high school cumulative grade point average (G.P.A.). The teachers obtain a random sample of students and determine the average number of hours each student studies along with the student's cumulative high school G.P.A. Construct a 95% confidence interval for the true slope of the regression line to help answer the teachers' question. Figure 10.1 presents a data table containing the average number of hours studied per week and the corresponding G.P.A for the 20 high-school students in the sample, along with a scatterplot of the data. GPA 2 1 0 Scatter Plot 000 0 2 4 6 8 10 12 Ave_Hrs 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Ave Hrs 10.5 3.0 6.5 8.0 8.5 2.5 9.5 1.0 4.6 3.5 2.2 6.0 8.0 6.0 5.0 3.0 5.0 4.0 9.0 7.0 GPA 4.571 2.800 3.888 4.055 3.920 3.134 4.445 1.777 2.770 3.112 2.308 3.665 4.500 3.333 3.100 2.723 3.888 3.500 4.334 3.388 Figure 10.1 A scatterplot of the data appears roughly linear with no apparent outliers.
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