Exam 2: The Simple Regression Model

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If a change in variable x causes a change in variable y, variable x is called the _____.

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Which of the following is an example of a dummy variable?

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The explained sum of squares for the regression function, The explained sum of squares for the regression function,   , is defined as _____. , is defined as _____.

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What does the equation What does the equation   denote if the regression equation is   ? denote if the regression equation is What does the equation   denote if the regression equation is   ? ?

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The sample covariance between the regressors and the Ordinary Least Square (OLS) residuals is always positive.

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In the equation In the equation   , what is the estimated value of   ? , what is the estimated value of In the equation   , what is the estimated value of   ? ?

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In the equation In the equation   , c denotes consumption and i denotes income. What is the residual for the 5<sup>th</sup> observation if   =$500 and   =$475? , c denotes consumption and i denotes income. What is the residual for the 5th observation if In the equation   , c denotes consumption and i denotes income. What is the residual for the 5<sup>th</sup> observation if   =$500 and   =$475? =$500 and In the equation   , c denotes consumption and i denotes income. What is the residual for the 5<sup>th</sup> observation if   =$500 and   =$475? =$475?

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Consider the following regression model: y = Consider the following regression model: y =   <sub>0</sub> +   <sub>1</sub>x<sub>1</sub> + u. Which of the following is a property of Ordinary Least Square (OLS) estimates of this model and their associated statistics? 0 + Consider the following regression model: y =   <sub>0</sub> +   <sub>1</sub>x<sub>1</sub> + u. Which of the following is a property of Ordinary Least Square (OLS) estimates of this model and their associated statistics? 1x1 + u. Which of the following is a property of Ordinary Least Square (OLS) estimates of this model and their associated statistics?

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The sample correlation between xi and yi is denoted by _____.​

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Consider a simple linear regression model, y = β0+ β1x + u, . What does the zero conditional mean assumption imply?

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