In: Statistics and Probability
Please give a detailed explanation, not just the answer. Thanks in advance!
Use the data in the given table to fill in the missing
coefficients. Round your answers to 3 decimal places.
| x | y |
|---|---|
| 2 | 13.524 |
| 7.5 | 19.125 |
| 13 | 23.463 |
| 18.5 | 28.937 |
| 24 | 33.6 |
| 29.5 | 37.779 |
| 35 | 43.065 |
y=_____x +_______
Solution =
The regression is a way to model the relationship between two variables. ... The equation has the form Y= a + bX, where Y is the dependent variable (that's the variable that goes on the Y axis), X is the independent variable (i.e. it is plotted on the X axis), b is the slope of the line and a is the y-intercept.
| X | Y | XY | X^2 | Y^2 |
| 2 | 13.524 | 27.048 | 4 | 182.898576 |
| 7.5 | 19.125 | 143.4375 | 56.25 | 365.765625 |
| 13 | 23.463 | 305.019 | 169 | 550.512369 |
| 18.5 | 28.937 | 535.3345 | 342.25 | 837.349969 |
| 24 | 33.6 | 806.4 | 576 | 1128.96 |
| 29.5 | 37.779 | 1114.481 | 870.25 | 1427.25284 |
| 35 | 43.065 | 1507.275 | 1225 | 1854.59423 |

| n | 7 |
| sum(XY) | 4438.99 |
| sum(X) | 129.50 |
| sum(Y) | 199.49 |
| sum(X^2) | 3242.75 |
| sum(Y^2) | 6347.33 |
| Numerator | 5238.62 |
| Denominator | 5241.59 |
| r | 0.9994 |
| r square | 0.9989 |
| Xbar(mean) | 18.5000 |
| Ybar(mean) | 28.4990 |
| SD(X) | 9.3930 |
| SD(Y) | 8.3112 |
| b | 0.8836 |
| a | 12.1532 |
The regression equation,
= bx + a
= (0.884)x + 12.153
Answer :
= (0.884)x + 12.153