MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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Concept explainers

Unitary Method
The word “unitary” comes from the word “unit”, which means a single and complete entity. In this method, we find the value of a unit product from the given number of products, and then we solve for the other number of products.
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I need help with a, b and d
### Relationship Between Phone Usage and Woman's Weight **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 8 women are shown in the table below. **Data Table:** | | Time (minutes/day) | Weight (pounds) | |-----|--------------------|------------------| | 1 | 81 | 119 | | 2 | 52 | 119 | | 3 | 52 | 116 | | 4 | 64 | 117 | | 5 | 62 | 128 | | 6 | 23 | 105 | | 7 | 36 | 116 | | 8 | 30 | 105 | **Questions:** **a. Find the correlation coefficient: \( r = \)** Round to 2 decimal places. **b. The null and alternative hypotheses for correlation are:** \[ H_0: r = 0 \] \[ H_1: r \neq 0 \] The p-value is: \_\_\_\_ (Round to four decimal places) **c. Use a level of significance of \( \alpha = 0.05 \) to state the conclusion of the hypothesis test in the context of the study.** - [ ] 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. - [ ] 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. **d. \( r^2 = \)** (Round to two decimal places) **e. Interpret \( r^2 \):** - [ ] There is a 56% chance that the regression line will be a good predictor for women's weight based on their time
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Transcribed Image Text:### Relationship Between Phone Usage and Woman's Weight **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 8 women are shown in the table below. **Data Table:** | | Time (minutes/day) | Weight (pounds) | |-----|--------------------|------------------| | 1 | 81 | 119 | | 2 | 52 | 119 | | 3 | 52 | 116 | | 4 | 64 | 117 | | 5 | 62 | 128 | | 6 | 23 | 105 | | 7 | 36 | 116 | | 8 | 30 | 105 | **Questions:** **a. Find the correlation coefficient: \( r = \)** Round to 2 decimal places. **b. The null and alternative hypotheses for correlation are:** \[ H_0: r = 0 \] \[ H_1: r \neq 0 \] The p-value is: \_\_\_\_ (Round to four decimal places) **c. Use a level of significance of \( \alpha = 0.05 \) to state the conclusion of the hypothesis test in the context of the study.** - [ ] 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. - [ ] 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. **d. \( r^2 = \)** (Round to two decimal places) **e. Interpret \( r^2 \):** - [ ] There is a 56% chance that the regression line will be a good predictor for women's weight based on their time
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