Duplicate Question
The question on this page has been marked as a duplicate question.
Original Question
Create a linear model for the data in the table. x 2 6 9 10 11 13 17 y 7 10 14 17 18 21 27 Question content area bottom Part 1...Question
Create a linear model for the data in the table.
x
3
7
10
11
12
14
18
y
5
10
15
17
18
21
26
Question content area bottom
Part 1
Write a linear model for the data in the table.
yequals
enter your response herexplus(
enter your response here)
(Type an integer or decimal rounded to three decimal places as needed.)
x
3
7
10
11
12
14
18
y
5
10
15
17
18
21
26
Question content area bottom
Part 1
Write a linear model for the data in the table.
yequals
enter your response herexplus(
enter your response here)
(Type an integer or decimal rounded to three decimal places as needed.)
Answers
There are no human answers yet.
Answered by
GPT-4o mini
To create a linear model \( y = mx + b \) from the provided data points, we first need to calculate the slope \( m \) and the y-intercept \( b \).
1. **Data Points**: You provided the following pairs:
- (3, 5)
- (7, 10)
- (10, 15)
- (11, 17)
- (12, 18)
- (14, 21)
- (18, 26)
2. **Calculating the Slope \( m \)**:
The formula for the slope \( m \) is:
\[
m = \frac{n(\sum xy) - (\sum x)(\sum y)}{n(\sum x^2) - (\sum x)^2}
\]
where \( n \) is the number of data points, \( \sum xy \) is the sum of the product of each x and y pair, \( \sum x \) is the sum of the x values, \( \sum y \) is the sum of the y values, and \( \sum x^2 \) is the sum of the squares of the x values.
Let's calculate these values:
- \( n = 7 \)
- \( \sum x = 3 + 7 + 10 + 11 + 12 + 14 + 18 = 85 \)
- \( \sum y = 5 + 10 + 15 + 17 + 18 + 21 + 26 = 112 \)
- \( \sum xy = (3*5) + (7*10) + (10*15) + (11*17) + (12*18) + (14*21) + (18*26) \)
\[
= 15 + 70 + 150 + 187 + 216 + 294 + 468 = 1400
\]
- \( \sum x^2 = 3^2 + 7^2 + 10^2 + 11^2 + 12^2 + 14^2 + 18^2 \)
\[
= 9 + 49 + 100 + 121 + 144 + 196 + 324 = 943
\]
Now plugging these values into the slope formula:
\[
m = \frac{7(1400) - (85)(112)}{7(943) - (85)^2}
\]
\[
= \frac{9800 - 9520}{6601 - 7225} = \frac{280}{-624} = -0.449
\]
3. **Calculating the y-Intercept \( b \)**:
The formula to find \( b \) is:
\[
b = \frac{\sum y - m \sum x}{n}
\]
Plugging the values into this formula:
\[
b = \frac{112 - (-0.449)(85)}{7}
\]
\[
= \frac{112 + 38.165}{7} = \frac{150.165}{7} = 21.38
\]
4. **Final Model**:
The linear model can be summarized as:
\[
y = -0.449x + 21.38
\]
### Final Answer:
Thus, the linear model in the required format is:
\[
y = -0.449x + 21.38
\]
Feel free to make adjustments or round the numbers to your required precision!
1. **Data Points**: You provided the following pairs:
- (3, 5)
- (7, 10)
- (10, 15)
- (11, 17)
- (12, 18)
- (14, 21)
- (18, 26)
2. **Calculating the Slope \( m \)**:
The formula for the slope \( m \) is:
\[
m = \frac{n(\sum xy) - (\sum x)(\sum y)}{n(\sum x^2) - (\sum x)^2}
\]
where \( n \) is the number of data points, \( \sum xy \) is the sum of the product of each x and y pair, \( \sum x \) is the sum of the x values, \( \sum y \) is the sum of the y values, and \( \sum x^2 \) is the sum of the squares of the x values.
Let's calculate these values:
- \( n = 7 \)
- \( \sum x = 3 + 7 + 10 + 11 + 12 + 14 + 18 = 85 \)
- \( \sum y = 5 + 10 + 15 + 17 + 18 + 21 + 26 = 112 \)
- \( \sum xy = (3*5) + (7*10) + (10*15) + (11*17) + (12*18) + (14*21) + (18*26) \)
\[
= 15 + 70 + 150 + 187 + 216 + 294 + 468 = 1400
\]
- \( \sum x^2 = 3^2 + 7^2 + 10^2 + 11^2 + 12^2 + 14^2 + 18^2 \)
\[
= 9 + 49 + 100 + 121 + 144 + 196 + 324 = 943
\]
Now plugging these values into the slope formula:
\[
m = \frac{7(1400) - (85)(112)}{7(943) - (85)^2}
\]
\[
= \frac{9800 - 9520}{6601 - 7225} = \frac{280}{-624} = -0.449
\]
3. **Calculating the y-Intercept \( b \)**:
The formula to find \( b \) is:
\[
b = \frac{\sum y - m \sum x}{n}
\]
Plugging the values into this formula:
\[
b = \frac{112 - (-0.449)(85)}{7}
\]
\[
= \frac{112 + 38.165}{7} = \frac{150.165}{7} = 21.38
\]
4. **Final Model**:
The linear model can be summarized as:
\[
y = -0.449x + 21.38
\]
### Final Answer:
Thus, the linear model in the required format is:
\[
y = -0.449x + 21.38
\]
Feel free to make adjustments or round the numbers to your required precision!
Submit Your Answer
We prioritize human answers over AI answers.
If you are human, and you can answer this question, please submit your answer.