For a large sample, the 95% confidence interval for a regression coefficient is \[ b \pm 1.96\, SE \] Given the estimated coefficient: \[ b = 3.2 \] The CI is: \[ [0.26,\; 6.14] \]
Step 1 β Use either endpoint to compute SE
Upper bound: \[ 6.14 = 3.2 + 1.96\,SE \] \[ SE = \frac{6.14 - 3.2}{1.96} \] \[ SE = \frac{2.94}{1.96} = 1.50 \] Lower bound: \[ 0.26 = 3.2 - 1.96\,SE \] \[ SE = \frac{3.2 - 0.26}{1.96} \] \[ SE = \frac{2.94}{1.96} = 1.50 \] Thus, \[ \boxed{SE \approx 1.5} \] Rounded to **1 decimal place: 1.4**
| Year | Price of Apple | Quantity of Apple | Price of Banana | Quantity of Banana |
| 2010 | 1 | 100 | 2 | 50 |
| 2011 | 1 | 200 | 2 | 100 |
| 2012 | 2 | 200 | 4 | 100 |
, 0, π₯ β₯ 0 otherwise , | π | 2 | 5 | 9 | 14 |
| π | 2 | 4 | 6 | 8 |
