Our prediction is best when we minimize the distance between the regression line and ___: a. our data points b. the number of our participants c. we do not want to ever minimize the distance between the regression line and anything d. our predicted data points
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The question is about regression analysis, which is a statistical method used to model the relationship between a dependent variable and one or more independent variables. The goal of regression analysis is to create a model that best predicts the dependent Show more…
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The basic assumption behind regression analysis is: a- To estimate a line that goes through most values in the observed data set b- To minimize the sum of the squared residuals c- Estimate a line that maximizes the difference between the sum of yᵢ-yᵢ d- All of them What is the answer?
Diwakar M.
The line of "best fit" in linear regression is derived by: Minimizing the sum of vertical squared distances from each data point to the projected point on the line Minimizing the sum of horizontal squared distances from each data point to the projected point on the line Maximizing the sum of vertical squared distances from each data point to the projected point on the line None of the answers is correct
David N.
The least squares regression line – that is, the regression line obtained using the method of least squares – is: Select one: a. the line which best splits the data in half, with 50% of the data points lying above the regression. line and 50% of the data points lying below the regression line. b. the line which makes the correlation coefficient as close to +1 or –1 as possible. c. the line which guarantees that the independent variable y will be normally distributed. d. the line which minimizes the number of data points that do not pass through the regression line. e. the line which makes the sum of the squared vertical differences between the observed values and predicted values as small as possible.
Adi S.
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