Which of the following is FALSE? - O The regression model assumes the errors (residuals) are normally distributed. O Data point below the regression line, the residual is negative. The errors (residuals) in a regression model are assumed to have a zero mean. O The errors (residuals) in a regression model are assumed to have increasing mear

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Which of the following is FALSE? *
The regression model assumes the errors (residuals) are normally distributed.
Data point below the regression line, the residual is negative.
The errors (residuals) in a regression model are assumed to have a zero mean.
The errors (residuals) in a regression model are assumed to have increasing mean.
In regression analysis, the regression line
Minimize the sum of distances between the actual value x and the predicted x values.
Minimize the perpendicular distance between the regression line and each data point.
Minimize the sum of the squared residuals between the actual x and the predicted x
values.
Minimize the sum of the squared residuals between the actual y and the predicted y
values.
The smaller the distance between observed data points and the regression
line, the smaller the sum of squares regression (SSR).
TRUE
FALSE
Transcribed Image Text:Which of the following is FALSE? * The regression model assumes the errors (residuals) are normally distributed. Data point below the regression line, the residual is negative. The errors (residuals) in a regression model are assumed to have a zero mean. The errors (residuals) in a regression model are assumed to have increasing mean. In regression analysis, the regression line Minimize the sum of distances between the actual value x and the predicted x values. Minimize the perpendicular distance between the regression line and each data point. Minimize the sum of the squared residuals between the actual x and the predicted x values. Minimize the sum of the squared residuals between the actual y and the predicted y values. The smaller the distance between observed data points and the regression line, the smaller the sum of squares regression (SSR). TRUE FALSE
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