Keyword | CPC | PCC | Volume | Score | Length of keyword |
---|---|---|---|---|---|
sklearn linear regression documentation | 0.98 | 0.7 | 3471 | 38 | 39 |
sklearn | 1.34 | 0.7 | 7534 | 83 | 7 |
linear | 1.22 | 0.2 | 3602 | 53 | 6 |
regression | 1.07 | 0.8 | 9047 | 10 | 10 |
documentation | 0.92 | 0.4 | 5402 | 37 | 13 |
Keyword | CPC | PCC | Volume | Score |
---|---|---|---|---|
sklearn linear regression documentation | 0.61 | 0.5 | 4101 | 48 |
sklearn simple linear regression | 0.65 | 0.1 | 8075 | 70 |
Simple linear regression is a technique that we can use to understand the relationship between one predictor variable and a response variable.. This technique finds a line that best “fits” the data and takes on the following form: ŷ = b 0 + b 1 x. where: ŷ: The estimated response value; b 0: The intercept of the regression line; b 1: The slope of the regression line
How is hypothesis testing used in linear regression?We perform a hypothesis test of the "significance of the correlation coefficient" to decide whether the linear relationship in the sample data is strong enough to use to model the relationship in the population. The sample data are used to compute r, the correlation coefficient for the sample.