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Answer: The effects of independent variables not included in the model
$\varepsilon_i$ denotes the effects of independent variables other than the variable of interest to the researcher, which nonetheless impact the dependent variable. For example, assume you want to assess the effect of class size (independent variable) on student performance (dependent variable): the error term might comprise factors such as teacher quality, student economic background, or even luck.
Author: Nikitesh Somanthe
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The relationship between two variables can be explained by the following regression function:
What does represent?
A
The difference between total variation and the explained variation
B
The effects of independent variables not included in the model
C
The slope coefficient
D
The intercept coefficient