What is a residual? What does it mean when a residual is positive? Choose the correct answer below. A. a residual is the difference between an observed value of the response variable y and the average value of the response variable. If it is positive, then the response variable is greater than the mean. B. A residual is the difference between an observed value of the response variable y and the predicted value of y. If it ispositive, then the observed value is greater than the predicted value. C. A residual is the difference between an observed value of the response variable y and the value of the corresponding explanatory variable x. If it is positive, then the response variable is greater than the explanatory variable. D. A residual is a data point that does not fit the pattern of the rest of the data. If it is positive, then the data point should still be included in the data set.

Question

What is a​ residual? What does it mean when a residual is ​positive?  Choose the correct answer below.  A. a residual is the difference between an observed value of the response variable y and the average value of the response variable. If it is​ positive, then the response variable is greater than the mean.  B. A residual is the difference between an observed value of the response variable y and the predicted value of y. If it is​positive, then the observed value is greater than the predicted value.  C. A residual is the difference between an observed value of the response variable y and the value of the corresponding explanatory variable x. If it is​ positive, then the response variable is greater than the explanatory variable.  D. A residual is a data point that does not fit the pattern of the rest of the data. If it is​ positive, then the data point should still be included in the data set.

Shannon Hodgkinson · Accepted Answer

A residual is the difference between an observed value and the expected value of the quantity of interest.   The answer is:   B. A residual is the difference between an observed value of the response variable y and the predicted value of y. If it is​ positive, then the observed value is greater than the predicted value.

Esta Hurtado · Accepted Answer

Solution:  Residual error in regression can be calculated as  Residual error ei = Yi - Yi^  Yi is the observed value of response variable Y.  Yi^ is the predicted value of Y using linear regression equation.  Residual error is the error that is not explained by the regression equation.  So residual error is the difference between an observed value of the response variable y and the predicted value of y. if residual is positive that means observed value is greater than predicted value. so it correct answer is C.

alenahelenash · Accepted Answer

Option D is Correct Explanation Because Residual = Actual or Observed Y value-Predicted value If Point is above the line, it means Observed value &amp;gt; Predicted value, So Residual is Positive If Point is Below the line, it means Observed value &amp;lt; Predicted value, So Residual is Negative

What is a residual? What does it mean when a residual is p

Answered question

Answer & Explanation

New Questions in Other