world:quiz1
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world:quiz1 [2025/09/30 00:25] rdouc created |
world:quiz1 [2025/09/30 19:02] (current) rdouc |
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| Which of the following statements are always true: | Which of the following statements are always true: | ||
| - | ^ Number ^ statement ^ | + | |
| - | | 1 | \(\sum_{i=1}^n (x_i-\bar x)=0\) | | + | ^ Number ^ statement ^ answer ^ |
| - | | 2 | \((\sum_{i=1}^n x_i)-\bar x=0\) | | + | | 1 | \(\sum_{i=1}^n (x_i-\bar x)=0\) | **TRUE** | |
| - | | 3 | The regression coefficient estimator \(\hat \beta_2\) is given by: \(\hat \beta_2=\frac{\sum_{i=1}^n x_i(y_i-\bar y)}{\sum_{i=1}^n (x_i-\bar x)^2}\) | | + | | 2 | \((\sum_{i=1}^n x_i)-\bar x=0\) | **FALSE** | |
| - | | 4 | The regression coefficient estimator \(\hat \beta_2\) is given by: \(\hat \beta_2=\frac{(\sum_{i=1}^n x_i y_i/n) -\bar x \bar y}{\sum_{i=1}^n x_i^2/n-(\bar x)^2}\) | | + | | 3 | The regression coefficient estimator \(\hat \beta_2\) is given by: \(\hat \beta_2=\frac{\sum_{i=1}^n x_i(y_i-\bar y)}{\sum_{i=1}^n (x_i-\bar x)^2}\) | **TRUE** | |
| - | | 5 | The regression coefficient estimator \(\hat \beta_2\) is given by: \(\hat \beta_2=\frac{(\sum_{i=1}^n x_i y_i) -\bar x \bar y}{(\sum_{i=1}^n x_i^2)-(\bar x)^2}\) | | + | | 4 | The regression coefficient estimator \(\hat \beta_2\) is given by: \(\hat \beta_2=\frac{(\sum_{i=1}^n x_i y_i/n) -\bar x \bar y}{\sum_{i=1}^n x_i^2/n-(\bar x)^2}\) | **TRUE** | |
| - | | 6 | The regression line is defined by the equation \(y=\beta_1 + \beta_2 x\). | | + | | 5 | The regression coefficient estimator \(\hat \beta_2\) is given by: \(\hat \beta_2=\frac{(\sum_{i=1}^n x_i y_i) -\bar x \bar y}{(\sum_{i=1}^n x_i^2)-(\bar x)^2}\) | **FALSE** | |
| - | | 7 | The regression line is defined by the equation \(y=\hat \beta_1 +\hat \beta_2 x\). | | + | | 6 | The regression line is defined by the equation \(y=\beta_1 + \beta_2 x\). | **FALSE** | |
| - | | 8 | Assume that the regression line is \(y=5 x+4\). Assume that \(n=10\), \(\sum_{i=1}^n x_i=30\). Then, we obtain that \(\sum_{i=1}^n y_i=19\). | | + | | 7 | The regression line is defined by the equation \(y=\hat \beta_1 +\hat \beta_2 x\). | **TRUE** | |
| - | | 9 | Assume that the regression line is \(y=5 x+4\). Assume that \(n=10\), \(\sum_{i=1}^n x_i=30\). Then, we obtain that \(\sum_{i=1}^n y_i=190\). | | + | | 8 | Assume that the regression line is \(y=5 x+4\). Assume that \(n=10\), \(\sum_{i=1}^n x_i=30\). Then, we obtain that \(\sum_{i=1}^n y_i=19\). | **FALSE** | |
| - | | 10 | Assume that the regression line is \(y=5 x+4\). Assume that \(n=10\), \(\sum_{i=1}^n x_i=30\). Then, we obtain that \(\sum_{i=1}^n y_i=154\). | | + | | 9 | Assume that the regression line is \(y=5 x+4\). Assume that \(n=10\), \(\sum_{i=1}^n x_i=30\). Then, we obtain that \(\sum_{i=1}^n y_i=190\). | **TRUE** | |
| + | | 10 | Assume that the regression line is \(y=5 x+4\). Assume that \(n=10\), \(\sum_{i=1}^n x_i=30\). Then, we obtain that \(\sum_{i=1}^n y_i=154\). | **FALSE** | | ||
world/quiz1.1759184742.txt.gz · Last modified: 2025/09/30 00:25 by rdouc
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