Twelve workers at a production line were asked to take a special three-day intensive course to improve their productivity. At the beginning and again at the end of the course, they were given a particular task to see the improvement in their productivity. Based on the data recorded for the two variables Number of years of experience X and Improvement (number of units per minute) Y, the following sums were calculated.

xi = 96, yi = 132, xi2 = 892, yi2 =1510, xiyi= 1110

Consider estimating a simple linear regression model of the form

y = b₁ + b₂x + e

Q5. The intercept term of the least-squares line, b₁, is

1. 7.25
2. 0.435
3. 7.52
4. 0.453

Q6. When the experience is 8 years and the word improvement is 12, then the corresponding least squares estimation residual is

1. 0
2. -1
3. 1
4. 11

Q7. The value of Sum of Squared Errors (SSE) for the above estimation is

1. 1.6
2. 35.4
3. 34.5
4. 0.63

Q8. The value of coefficient of determination (R²) in the above estimation is

1. 0.450
2. 0.504
3. 0.405
4. 0.595

Q9. An estimated standard error of the intercept coefficient b₁ is

1. 1.348
2. 0.167
3. 1.438
4. 0

Q10. To test results of the null hypothesis that H₀: β₂ = 0 against the alternative H_A: β₂ ≠ 0, the conclusion at 5 percent significant level is (select the best answer):

1. Reject the null hypothesis
2. Do not reject the null hypothesis
3. Number of years of experience significantly influences the productivity at the 5 percent level of significance
4. Number of years of experience does not significantly influence the productivity at the 5 percent level of significance

Answer rating: 100% (QA)

To solve the questions related to the simple linear regression model we can use the formulas and calculations based on the given data Here are the solutions Q5 The intercept term of the leastsquares l... View the full answer