What is the relationship between the amount of time statistics students study per week and their final exam scores? The results of the survey are shown below. Time 11 12 10 8 11 12 1 Score 90 81 85 89 82 95 7 59 86 16 95 a. Find the correlation coefficient: r = b. The null and alternative hypotheses for correlation are: Ho: ? = 0 H₁: ?0 Round to 2 decimal places. The p-value is: (Round to four decimal places) c. Use a level of significance of a = 0.05 to state the conclusion of the hypothesis test in the context of the study. O There is statistically significant evidence to conclude that a student who spends more time studying will score higher on the final exam than a student who spends less time studying. O There is statistically significant evidence to conclude that there is a correlation between the time spent studying and the score on the final exam. Thus, the regression line is useful. O There is statistically insignificant evidence to conclude that a student who spends more time studying will score higher on the final exam than a student who spends less time studying. O There is statistically insignificant evidence to conclude that there is a correlation between the time spent studying and the score on the final exam. Thus, the use of the regression line is not appropriate. (Round to two decimal places) d. ² = e. Interpret ²: O There is a large variation in the final exam scores that students receive, but if you only look at students who spend a fixed amount of time studying per week, this variation on average is reduced by 67%. O 67% of all students will receive the average score on the final exam. O There is a 67% chance that the regression line will be a good predictor for the final exam score based on the time spent studying. O Given any group that spends a fixed amount of time studying per week, 67% of all of those students will receive the predicted score on the final exam.

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
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Chapter4: Equations Of Linear Functions
Section4.5: Correlation And Causation
Problem 11PPS
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Question 3
<
>
What is the relationship between the amount of time statistics students study per week and their final
exam scores? The results of the survey are shown below.
7 16
Time 11 12 10 8 11 12 1
Score 90 81 85 89 82 95 59 86 95
a. Find the correlation coefficient: r =
b. The null and alternative hypotheses for correlation are:
Ho: ?
= 0
H₁: ? ✓ #0
The p-value is:
(Round to four decimal places)
c. Use a level of significance of a = 0.05 to state the conclusion of the hypothesis test in the context
of the study.
Round to 2 decimal places.
O There is statistically significant evidence to conclude that a student who spends more time
studying will score higher on the final exam than a student who spends less time studying.
O There is statistically significant evidence to conclude that there is a correlation between the
time spent studying and the score on the final exam. Thus, the regression line is useful.
O There is statistically insignificant evidence to conclude that a student who spends more time
studying will score higher on the final exam than a student who spends less time studying.
O There is statistically insignificant evidence to conclude that there is a correlation between the
time spent studying and the score on the final exam. Thus, the use of the regression line is not
appropriate.
(Round to two decimal places)
d. ²
e. Interpret ²:
O There is a large variation in the final exam scores that students receive, but if you only look
students who spend a fixed amount of time studying per week, this variation on average is
reduced by 67%.
O 67% of all students will receive the average score on the final exam.
O There is a 67% chance that the regression line will be a good predictor for the final exam score
based on the time spent studying.
O Given any group that spends a fixed amount of time studying per week, 67% of all of those
students will receive the predicted score on the final exam.
Transcribed Image Text:Question 3 < > What is the relationship between the amount of time statistics students study per week and their final exam scores? The results of the survey are shown below. 7 16 Time 11 12 10 8 11 12 1 Score 90 81 85 89 82 95 59 86 95 a. Find the correlation coefficient: r = b. The null and alternative hypotheses for correlation are: Ho: ? = 0 H₁: ? ✓ #0 The p-value is: (Round to four decimal places) c. Use a level of significance of a = 0.05 to state the conclusion of the hypothesis test in the context of the study. Round to 2 decimal places. O There is statistically significant evidence to conclude that a student who spends more time studying will score higher on the final exam than a student who spends less time studying. O There is statistically significant evidence to conclude that there is a correlation between the time spent studying and the score on the final exam. Thus, the regression line is useful. O There is statistically insignificant evidence to conclude that a student who spends more time studying will score higher on the final exam than a student who spends less time studying. O There is statistically insignificant evidence to conclude that there is a correlation between the time spent studying and the score on the final exam. Thus, the use of the regression line is not appropriate. (Round to two decimal places) d. ² e. Interpret ²: O There is a large variation in the final exam scores that students receive, but if you only look students who spend a fixed amount of time studying per week, this variation on average is reduced by 67%. O 67% of all students will receive the average score on the final exam. O There is a 67% chance that the regression line will be a good predictor for the final exam score based on the time spent studying. O Given any group that spends a fixed amount of time studying per week, 67% of all of those students will receive the predicted score on the final exam.
f. The equation of the linear regression line is:
(Please show your answers to two decimal places)
g. Use the model to predict the final exam score for a student who spends 10 hours per week studying.
Final exam score =
(Please round your answer to the nearest whole number.)
h. Interpret the slope of the regression line in the context of the question:
+
O The slope has no practical meaning since you cannot predict what any individual student will
score on the final.
As x goes up, y goes up.
O For every additional hour per week students spend studying, they tend to score on averge 2.12
higher on the final exam.
i. Interpret the y-intercept in the context of the question:
O The y-intercept has no practical meaning for this study.
The average final exam score is predicted to be 64.
O The best prediction for a student who doesn't study at all is that the student will score 64 on
the final exam.
O If a student does not study at all, then that student will score 64 on the final exam.
Transcribed Image Text:f. The equation of the linear regression line is: (Please show your answers to two decimal places) g. Use the model to predict the final exam score for a student who spends 10 hours per week studying. Final exam score = (Please round your answer to the nearest whole number.) h. Interpret the slope of the regression line in the context of the question: + O The slope has no practical meaning since you cannot predict what any individual student will score on the final. As x goes up, y goes up. O For every additional hour per week students spend studying, they tend to score on averge 2.12 higher on the final exam. i. Interpret the y-intercept in the context of the question: O The y-intercept has no practical meaning for this study. The average final exam score is predicted to be 64. O The best prediction for a student who doesn't study at all is that the student will score 64 on the final exam. O If a student does not study at all, then that student will score 64 on the final exam.
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