Enter two data sets and this calculator will find the equation of the regression line and correlation coefficient. The calculator will generate a step by step explanation along with the graphic representation of the data sets and regression line.
solution
You entered the following data:
$$\begin{array}{c|cccccccccccccccccccccccccccccccccccccccccccccccccccccccccccc}X&1.1174&1.1311&1.1339&1.1099&1.1092&1.0859&1.0877&1.0736&1.1235&1.1221&1.1139&1.0995&1.1213&1.1149&1.0779&1.0837&1.1349&1.1621&1.2331&1.2472&1.2672&1.2901&1.3316&1.3539&1.3592&1.3732&1.3812&1.3822&1.3658&1.3610&1.3703&1.3492&1.3634&1.3347&1.3309&1.3080&1.3188&1.2982&1.3026&1.2963&1.3359&1.3288&1.3119&1.2827&1.2974&1.2855&1.2399&1.2288&1.2526&1.2788&1.3161&1.3201&1.3224&1.2904&1.3179&1.3555&1.3706&1.3770&1.4343&1.4264\\Y&95.42&95.88&93.05&94.58&98.22&99.65&98.75&100.21&97.02&96.48&95.85&97.44&95.66&96.99&94.71&98.66&95.32&95.00&90.65&88.41&87.02&86.05&82.78&81.52&79.81&80.40&79.53&80.25&79.72&81.40&80.19&80.66&80.26&80.32&82.14&81.54&83.38&83.40&81.81&83.17&82.00&79.23&79.87&80.16&79.99&80.03&81.22&82.71&81.75&83.13&78.85&79.14&78.79&79.42&80.52&78.49&76.31&79.08&74.17&74.04\end{array}$$The equation of the regression line is:
$$y~=~172.7 ~-~ 69.05 \cdot x$$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.
$X$ | $Y$ | $X\cdot Y$ | $X \cdot X$ |
1.1174 | 95.42 | 106.622308 | 1.24858276 |
1.1311 | 95.88 | 108.449868 | 1.27938721 |
1.1339 | 93.05 | 105.509395 | 1.28572921 |
1.1099 | 94.58 | 104.974342 | 1.23187801 |
1.1092 | 98.22 | 108.945624 | 1.23032464 |
1.0859 | 99.65 | 108.209935 | 1.17917881 |
1.0877 | 98.75 | 107.410375 | 1.18309129 |
1.0736 | 100.21 | 107.585456 | 1.15261696 |
1.1235 | 97.02 | 109.00197 | 1.26225225 |
1.1221 | 96.48 | 108.260208 | 1.25910841 |
1.1139 | 95.85 | 106.767315 | 1.24077321 |
1.0995 | 97.44 | 107.13528 | 1.20890025 |
1.1213 | 95.66 | 107.263558 | 1.25731369 |
1.1149 | 96.99 | 108.134151 | 1.24300201 |
1.0779 | 94.71 | 102.087909 | 1.16186841 |
1.0837 | 98.66 | 106.917842 | 1.17440569 |
1.1349 | 95.32 | 108.178668 | 1.28799801 |
1.1621 | 95.00 | 110.3995 | 1.35047641 |
1.2331 | 90.65 | 111.780515 | 1.52053561 |
1.2472 | 88.41 | 110.264952 | 1.55550784 |
1.2672 | 87.02 | 110.271744 | 1.60579584 |
1.2901 | 86.05 | 111.013105 | 1.66435801 |
1.3316 | 82.78 | 110.229848 | 1.77315856 |
1.3539 | 81.52 | 110.369928 | 1.83304521 |
1.3592 | 79.81 | 108.477752 | 1.84742464 |
1.3732 | 80.40 | 110.40528 | 1.88567824 |
1.3812 | 79.53 | 109.846836 | 1.90771344 |
1.3822 | 80.25 | 110.92155 | 1.91047684 |
1.3658 | 79.72 | 108.881576 | 1.86540964 |
1.3610 | 81.40 | 110.7854 | 1.852321 |
1.3703 | 80.19 | 109.884357 | 1.87772209 |
1.3492 | 80.66 | 108.826472 | 1.82034064 |
1.3634 | 80.26 | 109.426484 | 1.85885956 |
1.3347 | 80.32 | 107.203104 | 1.78142409 |
1.3309 | 82.14 | 109.320126 | 1.77129481 |
1.3080 | 81.54 | 106.65432 | 1.710864 |
1.3188 | 83.38 | 109.961544 | 1.73923344 |
1.2982 | 83.40 | 108.26988 | 1.68532324 |
1.3026 | 81.81 | 106.565706 | 1.69676676 |
1.2963 | 83.17 | 107.813271 | 1.68039369 |
1.3359 | 82.00 | 109.5438 | 1.78462881 |
1.3288 | 79.23 | 105.280824 | 1.76570944 |
1.3119 | 79.87 | 104.781453 | 1.72108161 |
1.2827 | 80.16 | 102.821232 | 1.64531929 |
1.2974 | 79.99 | 103.779026 | 1.68324676 |
1.2855 | 80.03 | 102.878565 | 1.65251025 |
1.2399 | 81.22 | 100.704678 | 1.53735201 |
1.2288 | 82.71 | 101.634048 | 1.50994944 |
1.2526 | 81.75 | 102.40005 | 1.56900676 |
1.2788 | 83.13 | 106.306644 | 1.63532944 |
Step 2: Find the sum of every column:
$$ \sum{X} = 75.5936 ~,~ \sum{Y} = 5142.2 ~,~ \sum{X \cdot Y} = 6432.067273 ~,~ \sum{X^2} = 95.91407284 $$Step 3: Use the following equations to find $a$ and $b$:
$$ \begin{aligned} a &= \frac{\sum{Y} \cdot \sum{X^2} - \sum{X} \cdot \sum{XY} }{n \cdot \sum{X^2} - \left(\sum{X}\right)^2} = \frac{ 5142.2 \cdot 95.91407284 - 75.5936 \cdot 6432.067273}{ 60 \cdot 95.91407284 - 75.5936^2} \approx 172.7 \\ \\b &= \frac{ n \cdot \sum{XY} - \sum{X} \cdot \sum{Y}}{n \cdot \sum{X^2} - \left(\sum{X}\right)^2} = \frac{ 60 \cdot 6432.067273 - 75.5936 \cdot 5142.2 }{ 60 \cdot 95.91407284 - \left( 75.5936 \right)^2} \approx -69.05\end{aligned}$$Step 4: Substitute $a$ and $b$ in regression equation formula
$$ \begin{aligned} y~&=~a ~+~ b \cdot x \\y~&=~172.7 ~-~ 69.05 \cdot x\end{aligned}$$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.
Please tell me how can I make this better.