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Question
this question has two parts. first, answer part a. then, answer part b.
part a
farming some crops, such as barley, are very sensitive to how acidic the soil is. barley grows best in soil with a ph range of 6 to 7.5. to determine the ideal level of acidity, a farmer measures how many bushels of barley he harvests in different fields with varying acidity levels.
| soil acidity (ph) | 5.7 | 6.2 | 6.6 | 6.8 | 7.1 |
|---|
a. find the equation for the best - fit line for the data and the correlation coefficient. round to the nearest hundredth, if necessary.
y = \boxed{}x + \boxed{}
Step 1: Identify variables and data points
Let \( x \) be the soil acidity (pH) and \( y \) be the bushels harvested. The data points are: \((5.7, 3)\), \((6.2, 20)\), \((6.6, 48)\), \((6.8, 61)\), \((7.1, 73)\).
Step 2: Calculate necessary sums
First, calculate \( \sum x \), \( \sum y \), \( \sum xy \), \( \sum x^2 \):
- \( \sum x = 5.7 + 6.2 + 6.6 + 6.8 + 7.1 = 32.4 \)
- \( \sum y = 3 + 20 + 48 + 61 + 73 = 205 \)
- \( \sum xy = (5.7 \times 3) + (6.2 \times 20) + (6.6 \times 48) + (6.8 \times 61) + (7.1 \times 73) \)
\( = 17.1 + 124 + 316.8 + 414.8 + 518.3 = 1391 \)
- \( \sum x^2 = (5.7)^2 + (6.2)^2 + (6.6)^2 + (6.8)^2 + (7.1)^2 \)
\( = 32.49 + 38.44 + 43.56 + 46.24 + 50.41 = 211.14 \)
Step 3: Calculate slope (\( m \)) and y-intercept (\( b \))
The formula for the slope \( m \) of the best - fit line \( y = mx + b \) is:
\( m=\frac{n\sum xy-\sum x\sum y}{n\sum x^{2}-(\sum x)^{2}} \)
where \( n = 5 \) (number of data points).
Substitute the values:
\( m=\frac{5\times1391 - 32.4\times205}{5\times211.14-(32.4)^{2}} \)
First, calculate the numerator: \( 5\times1391=6955 \), \( 32.4\times205 = 32.4\times(200 + 5)=6480+162 = 6642 \)
Numerator: \( 6955 - 6642=313 \)
Denominator: \( 5\times211.14 = 1055.7 \), \( (32.4)^{2}=32.4\times32.4 = 1049.76 \)
Denominator: \( 1055.7-1049.76 = 5.94 \)
\( m=\frac{313}{5.94}\approx52.69 \)
The formula for the y - intercept \( b \) is:
\( b=\frac{\sum y - m\sum x}{n} \)
Substitute the values:
\( \sum y=205 \), \( m\approx52.69 \), \( \sum x = 32.4 \), \( n = 5 \)
\( b=\frac{205-52.69\times32.4}{5} \)
\( 52.69\times32.4 = 52.69\times(30 + 2.4)=1580.7+126.456 = 1707.156 \)
\( b=\frac{205 - 1707.156}{5}=\frac{-1502.156}{5}\approx - 300.43 \)
Step 4: Calculate correlation coefficient (\( r \))
The formula for the correlation coefficient \( r \) is:
\( r=\frac{n\sum xy-\sum x\sum y}{\sqrt{[n\sum x^{2}-(\sum x)^{2}][n\sum y^{2}-(\sum y)^{2}]}} \)
First, calculate \( \sum y^{2}=(3)^{2}+(20)^{2}+(48)^{2}+(61)^{2}+(73)^{2}=9 + 400+2304 + 3721+5329 = 11763 \)
Substitute the values:
Numerator: \( 5\times1391-32.4\times205 = 313 \) (same as before)
Denominator part 1: \( \sqrt{[n\sum x^{2}-(\sum x)^{2}]}=\sqrt{5.94}\approx2.44 \)
Denominator part 2: \( \sqrt{[n\sum y^{2}-(\sum y)^{2}]}=\sqrt{5\times11763-(205)^{2}} \)
\( 5\times11763 = 58815 \), \( (205)^{2}=42025 \)
\( 58815 - 42025 = 16790 \), \( \sqrt{16790}\approx129.58 \)
Denominator: \( 2.44\times129.58\approx316.18 \)
\( r=\frac{313}{316.18}\approx0.99 \)
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The equation of the best - fit line is \( y\approx52.69x - 300.43 \) and the correlation coefficient \( r\approx0.99 \)
For the equation of the line, filling in the blanks: \( y=\boxed{52.69}x+\boxed{- 300.43} \) (and the correlation coefficient is approximately \( 0.99 \))