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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 6 16 8 12 Score 61 83 80 84 6 15 7 59 91 71 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 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. 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.

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 6 16 8 12 Score 61 83 80 84 6 15 7 59 91 71 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 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. 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.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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d. 7² = e. Interpret 7²: O 73% of all students will receive the average score on the final exam. O Given any group that spends a fixed amount of time studying per week, 73% of all of those students will receive the predicted score on the final exam. y time spent studying and the score on the final exam. Thus, the regression line is useful. (Round to two decimal places) = O There is a 73% chance that the regression line will be a good predictor for the final exam score based on the time spent studying. f. The equation of the linear regression line is: 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 73%. (Please show your answers to two decimal places) g. Use the model to predict the final exam score for a student who spends 6 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 As x goes up, y goes up. O The slope has no practical meaning since you cannot predict what any individual student will score on the final. O For every additional hour per week students spend studying, they tend to score on averge 2.44 higher on the final exam. i. Interpret the y-intercept in the context of the question: O If a student does not study at all, then that student will score 51 on the final exam. O The best prediction for a student who doesn't study at all is that the student will score 51 on the final exam. The y-intercept has no practical meaning for this study. O The average final exam score is predicted to be 51.
Transcribed Image Text:d. 7² = e. Interpret 7²: O 73% of all students will receive the average score on the final exam. O Given any group that spends a fixed amount of time studying per week, 73% of all of those students will receive the predicted score on the final exam. y time spent studying and the score on the final exam. Thus, the regression line is useful. (Round to two decimal places) = O There is a 73% chance that the regression line will be a good predictor for the final exam score based on the time spent studying. f. The equation of the linear regression line is: 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 73%. (Please show your answers to two decimal places) g. Use the model to predict the final exam score for a student who spends 6 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 As x goes up, y goes up. O The slope has no practical meaning since you cannot predict what any individual student will score on the final. O For every additional hour per week students spend studying, they tend to score on averge 2.44 higher on the final exam. i. Interpret the y-intercept in the context of the question: O If a student does not study at all, then that student will score 51 on the final exam. O The best prediction for a student who doesn't study at all is that the student will score 51 on the final exam. The y-intercept has no practical meaning for this study. O The average final exam score is predicted to be 51.
Question 33 < Time Score 61 83 80 > 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. 6 16 8 12 6 15 7 84 59 91 71 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 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. 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. (Round to two decimal places) d. 72 e. Interpret 7²: O 73% of all students will receive the average score on the final exam. O Given any group that spends a fixed amount of time studying per week, 73% of all of those students will receive the predicted score on the final exam. O There is a 73% chance that the regression line will be a good predictor for the final exam score based on the time spent studying. 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 73%. K
Transcribed Image Text:Question 33 < Time Score 61 83 80 > 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. 6 16 8 12 6 15 7 84 59 91 71 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 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. 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. (Round to two decimal places) d. 72 e. Interpret 7²: O 73% of all students will receive the average score on the final exam. O Given any group that spends a fixed amount of time studying per week, 73% of all of those students will receive the predicted score on the final exam. O There is a 73% chance that the regression line will be a good predictor for the final exam score based on the time spent studying. 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 73%. K
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