Regression Analysis
Produces the regression analysis of a data set
For more information on regression analysis, refer to the corresponding Wikipedia article.
Output Regression Type
Set the regression type. Three types are available:
-
Linear Regression: find a straight line in the form of y = a.x + b, where a is the slope and b is the intercept that best fits the data.
-
Logarithmic regression: find a logarithmic curve in the form of y = a.ln(x) + b, where a is the slope, b is the intercept and ln(x) is the natural logarithm of x, that best fits the data.
-
Power regression: Find a power curve in the form of y = a.x^b, where a is the coefficient, b is the power that best fits the data.
The results of the three types of regression analysis of the measurements in the table above are shown below.
|
Regression |
|||
|
Regression Model |
Linear |
Logarithmic |
Power |
|
R^2 |
0.1243901235 |
0.036283506 |
0.0884254697 |
|
Standard Error |
1.8692568609 |
1.9610483597 |
0.7746321053 |
|
Slope |
-0.2193939394 |
-0.4894112008 |
4.812672931 |
|
Intercept |
4.8666666667 |
4.3992268695 |
-0.3103085297 |
|
1 |
4.6472727273 |
4.3992268695 |
4.812672931 |
|
2 |
4.4278787879 |
4.0599928755 |
3.8812728356 |
|
3 |
4.2084848485 |
3.8615537101 |
3.4224061924 |
|
4 |
3.9890909091 |
3.7207588815 |
3.1301272785 |
|
5 |
3.7696969697 |
3.6115499281 |
2.9207204651 |
|
6 |
3.5503030303 |
3.5223197161 |
2.7600654308 |
|
7 |
3.3309090909 |
3.4468766468 |
2.6311476385 |
|
8 |
3.1115151515 |
3.3815248876 |
2.5243514679 |
|
9 |
2.8921212121 |
3.3238805506 |
2.4337544465 |
|
10 |
2.6727272727 |
3.2723159341 |
2.3554713075 |