How does the least squares method handle outliers in the data set?Select one:a.It removes themb.It ignores themc.It gives them more weightd.It gives them less weight
Question
How does the least squares method handle outliers in the data set?Select one:a.It removes themb.It ignores themc.It gives them more weightd.It gives them less weight
Solution
The least squares method handles outliers in the data set by giving them more weight. So, the correct answer is c. It gives them more weight. This is because the least squares method minimizes the sum of the squares of the residuals, and the squares of large residuals (which outliers tend to produce) are much larger than the squares of small residuals. Therefore, outliers can have a large effect on the least squares estimates.
Similar Questions
What does the least squares method aim to minimize?Select one:a.The sum of the squares of the errors between the data points and the line of best fitb.The mean of the data setc.The sum of the absolute values of the errors between the data points and the line of best fitd.The variance of the data set
Which of the following four modeling algorithms is least vulnerable to outlier bias? (Select one)A.Linear RegressionB.Naive BayesC.k-NND.GLM
What is the least squares method used for?Select one:a.To calculate the variance of a data setb.To find the line of best fit for a set of datac.To solve systems of linear equationsd.To calculate the mean of a data set
Which technique is used to reduce the impact of outliers in regression analysis? Winsorization Data transformation Cross-validation Regularization
Which technique is used to reduce the impact of outliers in regression analysis? Winsorization Data transformation Cross-validation Regularization
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