Enter two data sets and this calculator will find the equation of the regression line and corelation coefficient. The calculator will generate a step by step explanation along with the graphic representation of the data sets and regression line.
Result:
You entered the following data:
$$\begin{array}{c|cccccccccccc}X&95.42&95.88&93.05&94.58&98.22&99.65&98.75&100.21&97.02&96.48&95.85&97.44\\Y&48.91&49.10&45.92&38.34&33.75&33.62&37.04&41.65&46.59&45.09&49.20&47.12\end{array}$$The equation of the regression line is:
$$y~=~189.5 ~-~ 1.512 \cdot x$$The graph of the regression line is:
Explanation:
We will find an equation of the regression line in 4 steps.
Step 1: Find $X \cdot Y$ and $X^2$ as it was done in the table below.
$X$ | $Y$ | $X\cdot Y$ | $X \cdot X$ |
95.42 | 48.91 | 4666.9922 | 9104.9764 |
95.88 | 49.10 | 4707.708 | 9192.9744 |
93.05 | 45.92 | 4272.856 | 8658.3025 |
94.58 | 38.34 | 3626.1972 | 8945.3764 |
98.22 | 33.75 | 3314.925 | 9647.1684 |
99.65 | 33.62 | 3350.233 | 9930.1225 |
98.75 | 37.04 | 3657.7 | 9751.5625 |
100.21 | 41.65 | 4173.7465 | 10042.0441 |
97.02 | 46.59 | 4520.1618 | 9412.8804 |
96.48 | 45.09 | 4350.2832 | 9308.3904 |
95.85 | 49.20 | 4715.82 | 9187.2225 |
97.44 | 47.12 | 4591.3728 | 9494.5536 |
Step 2: Find the sum of every column:
$$ \sum{X} = 1162.55 ~,~ \sum{Y} = 516.33 ~,~ \sum{X \cdot Y} = 49947.9957 ~,~ \sum{X^2} = 112675.5741 $$Step 3: Use the following equations to find $a$ and $b$:
$$ \begin{aligned} a &= \frac{\sum{Y} \cdot \sum{X^2} - \sum{X} \cdot \sum{XY} }{n \cdot \sum{X^2} - \left(\sum{X}\right)^2} = \frac{ 516.33 \cdot 112675.5741 - 1162.55 \cdot 49947.9957}{ 12 \cdot 112675.5741 - 1162.55^2} \approx 189.5 \\ \\b &= \frac{ n \cdot \sum{XY} - \sum{X} \cdot \sum{Y}}{n \cdot \sum{X^2} - \left(\sum{X}\right)^2} = \frac{ 12 \cdot 49947.9957 - 1162.55 \cdot 516.33 }{ 12 \cdot 112675.5741 - \left( 1162.55 \right)^2} \approx -1.512\end{aligned}$$Step 4: Substitute $a$ and $b$ in regression equation formula
$$ \begin{aligned} y~&=~a ~+~ b \cdot x \\y~&=~189.5 ~-~ 1.512 \cdot x\end{aligned}$$Share this result with others by using the link below.
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Consider the following set of points: ${(-3 , -4), \, (2 , 3), \, (7 , 11)}$
a) Find the regression line for the given data points.
b) Plot the given points and the regression line.
The values of $X$ and their corresponding values of $Y$ are shown in the table below:
$$ \begin{array}{c|ccccc} X & ~1~ & ~2~ & ~3~ & ~4~ & ~5 \\ Y & ~4~ & ~8~ & ~9~ & ~11~& ~16 \end{array} $$Find a Pearson correlation coefficient.
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