Discover the answers you need at Westonci.ca, where experts provide clear and concise information on various topics. Discover detailed answers to your questions from a wide network of experts on our comprehensive Q&A platform. Get quick and reliable solutions to your questions from a community of experienced experts on our platform.
Sagot :
To find the equation of the regression line for the given data, follow these steps:
1. Observe the data:
- Days [tex]\( (x) \)[/tex]: 1, 2, 3, 4, 5, 6, 7
- Number of visitors [tex]\( (y) \)[/tex]: 120, 124, 130, 131, 135, 132, 135
2. Determine the linear relationship:
- We want to determine the best fit line [tex]\( y = mx + b \)[/tex], where [tex]\( m \)[/tex] is the slope and [tex]\( b \)[/tex] is the y-intercept.
3. Calculate the slope and intercept:
- Using the given data and applying statistical methods, like linear regression, the slope ([tex]\( m \)[/tex]) and intercept ([tex]\( b \)[/tex]) are calculated.
4. Result after calculation:
- The calculated slope [tex]\( m \)[/tex] is 2.4.
- The calculated intercept [tex]\( b \)[/tex] is 120.1.
5. Equation of the regression line:
- The equation of the regression line is [tex]\( y = 2.4x + 120.1 \)[/tex].
6. Verification with given options:
- Option A is [tex]\( y = 2.4x + 120.1 \)[/tex]
- Option B is [tex]\( y = 0.3x - 41.1 \)[/tex]
- Option C is [tex]\( y = 4x + 116 \)[/tex]
- Option D is [tex]\( y = 0.3x - 29 \)[/tex]
7. Matching the calculated equation:
- The correct equation that matches our calculation is given in Option A.
Therefore, the equation of the regression line for the given data is:
[tex]\[ \boxed{A.\; y = 2.4x + 120.1} \][/tex]
1. Observe the data:
- Days [tex]\( (x) \)[/tex]: 1, 2, 3, 4, 5, 6, 7
- Number of visitors [tex]\( (y) \)[/tex]: 120, 124, 130, 131, 135, 132, 135
2. Determine the linear relationship:
- We want to determine the best fit line [tex]\( y = mx + b \)[/tex], where [tex]\( m \)[/tex] is the slope and [tex]\( b \)[/tex] is the y-intercept.
3. Calculate the slope and intercept:
- Using the given data and applying statistical methods, like linear regression, the slope ([tex]\( m \)[/tex]) and intercept ([tex]\( b \)[/tex]) are calculated.
4. Result after calculation:
- The calculated slope [tex]\( m \)[/tex] is 2.4.
- The calculated intercept [tex]\( b \)[/tex] is 120.1.
5. Equation of the regression line:
- The equation of the regression line is [tex]\( y = 2.4x + 120.1 \)[/tex].
6. Verification with given options:
- Option A is [tex]\( y = 2.4x + 120.1 \)[/tex]
- Option B is [tex]\( y = 0.3x - 41.1 \)[/tex]
- Option C is [tex]\( y = 4x + 116 \)[/tex]
- Option D is [tex]\( y = 0.3x - 29 \)[/tex]
7. Matching the calculated equation:
- The correct equation that matches our calculation is given in Option A.
Therefore, the equation of the regression line for the given data is:
[tex]\[ \boxed{A.\; y = 2.4x + 120.1} \][/tex]
Thank you for visiting our platform. We hope you found the answers you were looking for. Come back anytime you need more information. Thank you for your visit. We're dedicated to helping you find the information you need, whenever you need it. Find reliable answers at Westonci.ca. Visit us again for the latest updates and expert advice.