Outliers can cause your model to be biased because they affect the values of the estimated regression coefficients. The change in this one point has a dramatic effect on the regression model chosen to fit the data. With the outlier present, the regression model changes – its gradient is reduced the line becomes flatter and …
With regression we strive to find the line that best describes the data collected, then estimate the gradient and intercept of the line. Having defined these values, we can insert different values of our predictor variable into the model to estimate the value of the outcome variable or dependent variable. A line that has a …
What is Regression? What is B? What is E? What are the regression coefficients? Read More »
The method of least squares is a way of finding the line that best fits the data (i.e. finding a line that goes through or as close to as many of the data point as possible). This ‘line of best fit’ is found by ascertaining which line, of all of the possible lines that could …