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What is the relationship between the number of minutes per day a woman spends talking on the phone and the woman's weight? The time on the phone and weight for 7 women are shown in the table below. Time 41 32 90 32 31 33 82 Pounds 131 112 144 104 113 120 142 a. Find the correlation coefficient: r = b. The null and alternative hypotheses for correlation are: Ho: ? = 0 H₁: 20 The p-value is: Round to 2 decimal places. (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. There is statistically insignificant evidence to conclude that there is a correlation between the time women spend on the phone and their weight. Thus, the use of the regression line is not appropriate. O There is statistically insignificant evidence to conclude that a woman who spends more time on the phone will weigh more than a woman who spends less time on the phone. O There is statistically significant evidence to conclude that there is a correlation between the time women spend on the phone and their weight. Thus, the regression line is useful. O There is statistically significant evidence to conclude that a woman who spends more time on the phone will weigh more than a woman who spends less time on the phone.

What is the relationship between the number of minutes per day a woman spends talking on the phone and the woman's weight? The time on the phone and weight for 7 women are shown in the table below. Time 41 32 90 32 31 33 82 Pounds 131 112 144 104 113 120 142 a. Find the correlation coefficient: r = b. The null and alternative hypotheses for correlation are: Ho: ? = 0 H₁: 20 The p-value is: Round to 2 decimal places. (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. There is statistically insignificant evidence to conclude that there is a correlation between the time women spend on the phone and their weight. Thus, the use of the regression line is not appropriate. O There is statistically insignificant evidence to conclude that a woman who spends more time on the phone will weigh more than a woman who spends less time on the phone. O There is statistically significant evidence to conclude that there is a correlation between the time women spend on the phone and their weight. Thus, the regression line is useful. O There is statistically significant evidence to conclude that a woman who spends more time on the phone will weigh more than a woman who spends less time on the phone.

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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**Transcription for Educational Website:** f. The equation of the linear regression line is: \(\hat{y} = \_\_\_\_ + \_\_\_\_x\) (Please show your answers to two decimal places) g. Use the model to predict the weight of a woman who spends 41 minutes on the phone. Weight = \_\_\_\_ (Please round your answer to the nearest whole number.) h. Interpret the slope of the regression line in the context of the question: - ○ For every additional minute women spend on the phone, they tend to weigh on average 0.54 additional pounds. - ○ As x goes up, y goes up. - ○ The slope has no practical meaning since you cannot predict a woman’s weight. i. Interpret the y-intercept in the context of the question: - ○ If a woman does not spend any time talking on the phone, then that woman will weigh 97 pounds. - ○ The average woman's weight is predicted to be 97. - ○ The y-intercept has no practical meaning for this study. - ○ The best prediction for the weight of a woman who does not spend any time talking on the phone is 97 pounds.
Transcribed Image Text:**Transcription for Educational Website:** f. The equation of the linear regression line is: \(\hat{y} = \_\_\_\_ + \_\_\_\_x\) (Please show your answers to two decimal places) g. Use the model to predict the weight of a woman who spends 41 minutes on the phone. Weight = \_\_\_\_ (Please round your answer to the nearest whole number.) h. Interpret the slope of the regression line in the context of the question: - ○ For every additional minute women spend on the phone, they tend to weigh on average 0.54 additional pounds. - ○ As x goes up, y goes up. - ○ The slope has no practical meaning since you cannot predict a woman’s weight. i. Interpret the y-intercept in the context of the question: - ○ If a woman does not spend any time talking on the phone, then that woman will weigh 97 pounds. - ○ The average woman's weight is predicted to be 97. - ○ The y-intercept has no practical meaning for this study. - ○ The best prediction for the weight of a woman who does not spend any time talking on the phone is 97 pounds.
**Title: Analyzing the Relationship Between Phone Usage and Weight in Women** **Research Question:** What is the relationship between the number of minutes per day a woman spends talking on the phone and the woman’s weight? The time on the phone and weight for 7 women are shown in the table below. | Time (min) | 41 | 32 | 90 | 32 | 31 | 33 | 82 | |------------|----|----|----|----|----|----|----| | Pounds | 131| 112| 144| 104| 113| 120| 142| **Study Tasks:** a. **Correlation Coefficient Calculation:** - Find the correlation coefficient \( r = \) [Blank] - (Round to 2 decimal places) b. **Hypothesis Testing:** - Null and alternative hypotheses for correlation are: - \( H_0: \rho = 0 \) - \( H_1: \rho \neq 0 \) - The p-value is: [Blank] - (Round to four decimal places) c. **Statistical Conclusion:** - Use a level of significance of \( \alpha = 0.05 \) to state the conclusion of the hypothesis test in the context of the study: - [Selected Option] There is statistically insignificant evidence to conclude that there is a correlation between the time women spend on the phone and their weight. Thus, the use of the regression line is not appropriate. - There is statistically insignificant evidence to conclude that a woman who spends more time on the phone will weigh more than a woman who spends less time on the phone. - There is statistically significant evidence to conclude that there is a correlation between the time women spend on the phone and their weight. Thus, the regression line is useful. - There is statistically significant evidence to conclude that a woman who spends more time on the phone will weigh more than a woman who spends less time on the phone. d. **Coefficient of Determination (\( r^2 \)):** - \( r^2 = \) [Blank] - (Round to two decimal places) e. **Interpretation of \( r^2 \):** - There is a 81% chance that the regression line will be a good predictor for women’s weight based on their time spent on the
Transcribed Image Text:**Title: Analyzing the Relationship Between Phone Usage and Weight in Women** **Research Question:** What is the relationship between the number of minutes per day a woman spends talking on the phone and the woman’s weight? The time on the phone and weight for 7 women are shown in the table below. | Time (min) | 41 | 32 | 90 | 32 | 31 | 33 | 82 | |------------|----|----|----|----|----|----|----| | Pounds | 131| 112| 144| 104| 113| 120| 142| **Study Tasks:** a. **Correlation Coefficient Calculation:** - Find the correlation coefficient \( r = \) [Blank] - (Round to 2 decimal places) b. **Hypothesis Testing:** - Null and alternative hypotheses for correlation are: - \( H_0: \rho = 0 \) - \( H_1: \rho \neq 0 \) - The p-value is: [Blank] - (Round to four decimal places) c. **Statistical Conclusion:** - Use a level of significance of \( \alpha = 0.05 \) to state the conclusion of the hypothesis test in the context of the study: - [Selected Option] There is statistically insignificant evidence to conclude that there is a correlation between the time women spend on the phone and their weight. Thus, the use of the regression line is not appropriate. - There is statistically insignificant evidence to conclude that a woman who spends more time on the phone will weigh more than a woman who spends less time on the phone. - There is statistically significant evidence to conclude that there is a correlation between the time women spend on the phone and their weight. Thus, the regression line is useful. - There is statistically significant evidence to conclude that a woman who spends more time on the phone will weigh more than a woman who spends less time on the phone. d. **Coefficient of Determination (\( r^2 \)):** - \( r^2 = \) [Blank] - (Round to two decimal places) e. **Interpretation of \( r^2 \):** - There is a 81% chance that the regression line will be a good predictor for women’s weight based on their time spent on the
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