Question
                Find the linear function that is the best fit for the data.
x
1
3
5
7
9
 
y
1
2
3
4
5
Question content area bottom
Part 1
What is the linear function of the data?
yequals
  
enter your response herexplus(
  
enter your response here)
(Type integers or decimals.)
            
        x
1
3
5
7
9
y
1
2
3
4
5
Question content area bottom
Part 1
What is the linear function of the data?
yequals
enter your response herexplus(
enter your response here)
(Type integers or decimals.)
Answers
                                                    There are no human answers yet.
                                            
                
                    Answered by
            GPT-4o mini
            
    To find the linear function that best fits the provided data points, we can use the method of least squares to determine the slope (m) and y-intercept (b) of the linear equation in the form \( y = mx + b \).
Given the data points:
\[
\begin{align*}
x: & \quad 1, 3, 5, 7, 9 \\
y: & \quad 1, 2, 3, 4, 5 \\
\end{align*}
\]
**Step 1: Calculate the means of \( x \) and \( y \)**
\[
\bar{x} = \frac{1 + 3 + 5 + 7 + 9}{5} = \frac{25}{5} = 5
\]
\[
\bar{y} = \frac{1 + 2 + 3 + 4 + 5}{5} = \frac{15}{5} = 3
\]
**Step 2: Calculate the slope (m)**
The formula for the slope \( m \) is:
\[
m = \frac{\sum (x_i - \bar{x})(y_i - \bar{y})}{\sum (x_i - \bar{x})^2}
\]
Next, we calculate each component:
\[
\begin{align*}
\sum (x_i - \bar{x})(y_i - \bar{y}) & = (1 - 5)(1 - 3) + (3 - 5)(2 - 3) + (5 - 5)(3 - 3) + (7 - 5)(4 - 3) + (9 - 5)(5 - 3) \\
& = (-4)(-2) + (-2)(-1) + (0)(0) + (2)(1) + (4)(2) \\
& = 8 + 2 + 0 + 2 + 8 = 20
\end{align*}
\]
\[
\sum (x_i - \bar{x})^2 = (1 - 5)^2 + (3 - 5)^2 + (5 - 5)^2 + (7 - 5)^2 + (9 - 5)^2 \\
= 16 + 4 + 0 + 4 + 16 = 40
\]
Now we can calculate \( m \):
\[
m = \frac{20}{40} = 0.5
\]
**Step 3: Calculate the y-intercept (b)**
The formula for the y-intercept \( b \) is:
\[
b = \bar{y} - m\bar{x}
\]
Substituting the values we have:
\[
b = 3 - 0.5 \cdot 5 = 3 - 2.5 = 0.5
\]
Finally, the equation of the linear function is:
\[
y = 0.5x + 0.5
\]
**Part 1 Answer:**
The linear function that best fits the data is:
\[
y = 0.5x + 0.5
\]
    
Given the data points:
\[
\begin{align*}
x: & \quad 1, 3, 5, 7, 9 \\
y: & \quad 1, 2, 3, 4, 5 \\
\end{align*}
\]
**Step 1: Calculate the means of \( x \) and \( y \)**
\[
\bar{x} = \frac{1 + 3 + 5 + 7 + 9}{5} = \frac{25}{5} = 5
\]
\[
\bar{y} = \frac{1 + 2 + 3 + 4 + 5}{5} = \frac{15}{5} = 3
\]
**Step 2: Calculate the slope (m)**
The formula for the slope \( m \) is:
\[
m = \frac{\sum (x_i - \bar{x})(y_i - \bar{y})}{\sum (x_i - \bar{x})^2}
\]
Next, we calculate each component:
\[
\begin{align*}
\sum (x_i - \bar{x})(y_i - \bar{y}) & = (1 - 5)(1 - 3) + (3 - 5)(2 - 3) + (5 - 5)(3 - 3) + (7 - 5)(4 - 3) + (9 - 5)(5 - 3) \\
& = (-4)(-2) + (-2)(-1) + (0)(0) + (2)(1) + (4)(2) \\
& = 8 + 2 + 0 + 2 + 8 = 20
\end{align*}
\]
\[
\sum (x_i - \bar{x})^2 = (1 - 5)^2 + (3 - 5)^2 + (5 - 5)^2 + (7 - 5)^2 + (9 - 5)^2 \\
= 16 + 4 + 0 + 4 + 16 = 40
\]
Now we can calculate \( m \):
\[
m = \frac{20}{40} = 0.5
\]
**Step 3: Calculate the y-intercept (b)**
The formula for the y-intercept \( b \) is:
\[
b = \bar{y} - m\bar{x}
\]
Substituting the values we have:
\[
b = 3 - 0.5 \cdot 5 = 3 - 2.5 = 0.5
\]
Finally, the equation of the linear function is:
\[
y = 0.5x + 0.5
\]
**Part 1 Answer:**
The linear function that best fits the data is:
\[
y = 0.5x + 0.5
\]
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