Regression refers to a data modeling technique which is used to analyze the relationship between measured and explanatory variables. The x - intercept of the graph is of no need in evaluating the suitability of a model.
- Residual plots are produced by plotting the difference in the actual and predicted values (residual) against the independent variables. A residual plot is expected to produce a random distribution of points else it is not appropriate if it shows a trend.
- The value of R-squared gives the percentage of variation in the model which is explained by the regression line, hence, the R-squared value is essential in determining the appropriateness of a model.
- A scatter plot is used to graph the trend or relationship between variables, such that one can visualize the pattern or relationship between them.
- The x - intercept is the value at the point where the regression line crosses the x - axis, this value has no significance in model selection, including the value of the y-intercept.
Therefore, the x - intercept is not a metric in determining if a model is appropriate or not for regression analysis.
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