A producer of educational TV shows for gifted children wants to promote the claim that gifted children's scores on an analytical test increase the more the children watch their shows. In RStudio, run the following code to install and/or library the package "openintro". 1. install.packages ("openintro") # don't do this again if you already did this! 2. library(openintro) 3. gifted Delete the install line of code if you are in an RMD file so that it doesn't install every time you knit. The last line of code will access the dataset of that name. The dataset named 'gifted' gives information about test scores of gifted children on a standard analytical test and the number of hours of educational TV these children watch. use the data set to make a model to predict score on analytical skills test ("score") from hours of educational TV watched per week ("edutv").

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Author:Amos Gilat
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A producer of educational TV shows for gifted children wants to promote the claim that gifted children's
scores on an analytical test increase the more the children watch their shows.
In RStudio, run the following code to install and/or library the package "openintro".
1. install.packages ("openintro") # don't do this again if you already did this!
2. library(openintro)
3. gifted
Delete the install line of code if you are in an RMD file so that it doesn't install every time you knit. The
last line of code will access the dataset of that name.
The dataset named 'gifted' gives information about test scores of gifted children on a standard analytical
test and the number of hours of educational TV these children watch. use the data set to make a model to
predict score on analytical skills test ("score") from hours of educational TV watched per week ("edutv").
a. Make a scatterplot of "score" (y-axis) vs "edutv" (x-axis). Which plot is the scatterplot?
Graph A Graph B Graph C Graph D
A
165-
160-
155-
150-
C₂0-
25-
20-
1.5-
10-
156
edutv
160
edutv
165
i. The hypotheses are:
Ho: ₁0
H₁:2₁ > 0
3.0
B
Ho B1 -3.067
HA: B1-3.067
D
165-
d. Interpret R².
160
156-
150-
165-
160
b. Does the relationship appear roughly linear?
155-
150-
O No, there are gaps in the graph along the x-axis.
O No, all the points do not fall on a straight line.
Yes, all the points fall on a straight line.
OYes, there is no obvious curvature in the graph
20
c. Do the data provide strong evidence that high school GPA and first-year college GPA are associated?
State the null and alternative hypotheses, report the p-value, and state your conclusion.
O Ho: #1 = 0
H₁₁0
edutv
30
edutv
O Ho: ₁-3.067
HA: ₁-3.067
Ho: B₁0
HA: 8₁> 0
ii. The p-value for the test is (round to three decimal places--if that value is 0 then enter 0.):
Ho: B₁ 0
HA: B₁0
iii. The result of this hypothesis test is:
O About 13.71% of the variation in hours of educational TV watched per week is explained
by the least-squares line.
O About 13.71% of the variation in score on analytical skills test is explained by the least-
squares line.
O hours of educational TV watched per week is predictive of score on analytical skills test.
O
e. What is the equation of the regression line?
O hoursty 165.144 score - 3.067
O score -3.067 hoursry + 165.144
O hoursty -3.067 score + 165.144
Oscore - 165.144 hoursry. 3.067
hours of educational TV watched per week is not predictive of score on analytical skills
test.
The total unexplained variation in the model.
O The amount of variation in hours of educational TV watched per week that is explained by the
least squares line.
O The total amount of variation in the model.
O the amount of variation in score on analytical skills test that is explained by the least squares
line.
f. Interpret the slope in the context of the model. For each [Select an answer V increase in
Select an answer
Select an answer
Select an answer
Select an answer
g. Interpret the y-intercept in the context of the model or explain why it should not be interpreted.
O When the score on analytical skills test of a gifted child is 0 the expected value of hours of
educational TV watched per week is 165.144.
O When the score on analytical skills test of a gifted child is 0 the expected value of hours of
per week.
educational TV watched per week is -3.067.
O It does not make sense to interpret the y-intercept for this model because no gifted child in
the data had a hours of educational TV watched per week anywhere close to 0.
O When the hours of educational TV watched per week of a gifted child is 0 the expected value
of score on analytical skills test is 165.144.
Transcribed Image Text:A producer of educational TV shows for gifted children wants to promote the claim that gifted children's scores on an analytical test increase the more the children watch their shows. In RStudio, run the following code to install and/or library the package "openintro". 1. install.packages ("openintro") # don't do this again if you already did this! 2. library(openintro) 3. gifted Delete the install line of code if you are in an RMD file so that it doesn't install every time you knit. The last line of code will access the dataset of that name. The dataset named 'gifted' gives information about test scores of gifted children on a standard analytical test and the number of hours of educational TV these children watch. use the data set to make a model to predict score on analytical skills test ("score") from hours of educational TV watched per week ("edutv"). a. Make a scatterplot of "score" (y-axis) vs "edutv" (x-axis). Which plot is the scatterplot? Graph A Graph B Graph C Graph D A 165- 160- 155- 150- C₂0- 25- 20- 1.5- 10- 156 edutv 160 edutv 165 i. The hypotheses are: Ho: ₁0 H₁:2₁ > 0 3.0 B Ho B1 -3.067 HA: B1-3.067 D 165- d. Interpret R². 160 156- 150- 165- 160 b. Does the relationship appear roughly linear? 155- 150- O No, there are gaps in the graph along the x-axis. O No, all the points do not fall on a straight line. Yes, all the points fall on a straight line. OYes, there is no obvious curvature in the graph 20 c. Do the data provide strong evidence that high school GPA and first-year college GPA are associated? State the null and alternative hypotheses, report the p-value, and state your conclusion. O Ho: #1 = 0 H₁₁0 edutv 30 edutv O Ho: ₁-3.067 HA: ₁-3.067 Ho: B₁0 HA: 8₁> 0 ii. The p-value for the test is (round to three decimal places--if that value is 0 then enter 0.): Ho: B₁ 0 HA: B₁0 iii. The result of this hypothesis test is: O About 13.71% of the variation in hours of educational TV watched per week is explained by the least-squares line. O About 13.71% of the variation in score on analytical skills test is explained by the least- squares line. O hours of educational TV watched per week is predictive of score on analytical skills test. O e. What is the equation of the regression line? O hoursty 165.144 score - 3.067 O score -3.067 hoursry + 165.144 O hoursty -3.067 score + 165.144 Oscore - 165.144 hoursry. 3.067 hours of educational TV watched per week is not predictive of score on analytical skills test. The total unexplained variation in the model. O The amount of variation in hours of educational TV watched per week that is explained by the least squares line. O The total amount of variation in the model. O the amount of variation in score on analytical skills test that is explained by the least squares line. f. Interpret the slope in the context of the model. For each [Select an answer V increase in Select an answer Select an answer Select an answer Select an answer g. Interpret the y-intercept in the context of the model or explain why it should not be interpreted. O When the score on analytical skills test of a gifted child is 0 the expected value of hours of educational TV watched per week is 165.144. O When the score on analytical skills test of a gifted child is 0 the expected value of hours of per week. educational TV watched per week is -3.067. O It does not make sense to interpret the y-intercept for this model because no gifted child in the data had a hours of educational TV watched per week anywhere close to 0. O When the hours of educational TV watched per week of a gifted child is 0 the expected value of score on analytical skills test is 165.144.
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