A regression model can be used to explain, predict and control the dependent variable, on the basis of independent variables.
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Q4: r2 is the square of the correlation
Q5: A least squares criterion minimizes the squared
Q6: The model: Y = Q7: The larger the beta coefficient value, the Q8: Correlation analysis provides a measure of the Q10: The total variation in Y, the dependent Q11: The unexplained variation in Y is estimated Q12: If a variable that is excluded from Q13: When testing the hypothesis that, in fact, Q14: An independent variable which takes a small
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