Data Analysis for Impact Evaluations – Quiz 2

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Question 1 of 5

1. Question
1. Which of the following statements about covariates in a regression with RCT data is true (assuming simple random assignment)? (select all that apply)
- Not controlling for covariates can lead to biased estimates
- Not controlling for covariates cannot lead to biased estimates
- Controlling for covariates can lead to more precise estimates
- Controlling for covariates cannot lead to more precise estimates
- Controlling for potential outcomes can lead to biased estimates
- Controlling for potential outcomes cannot lead to biased estimates
- None of the above
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Question 2 of 5

2. Question
Regress total Year 3 endline scores on treatment. Then regress total Year 3 endline scores on treatment and child_female.

2. Which of the following is the correct interpretation of the coefficient on child_female?
- Boys and girls score the same on average on the test
- Boys score higher on average than girls, and the difference is statistically significant at the 5% level
- Girls score higher on average than boys, and the difference is statistically significant at the 5% level
- Boys score higher on average than girls, but the difference is not statistically significant at the 5% level
- Girls score higher on average than boys, but the difference is not statistically significant at the 5% level
- None of the above
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Question 3 of 5

3. Question
3. Which of the following is the correct interpretation of the coefficient on treatment?
- Controlling for student gender has no impact on the estimate of the treatment effect
- Controlling for student gender increases the impact estimate, meaning that the previous impact estimate without controls was biased
- Controlling for student gender reduces the impact estimate, meaning that the previous impact estimate without controls was biased
- Controlling for student gender increases the impact estimate, but the previous impact estimate without controls was not biased
- Controlling for student gender reduces the impact estimate, but the previous impact estimate without controls was not biased
- None of the above
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Question 4 of 5

4. Question
Repeat the regression in the video with child_scst as a control but without dropping observations that are missing values for child_scst.

4. How many students were missing values for child_scst?
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Question 5 of 5

5. Question
5. Why is the standard error on the treatment coefficient smaller in this regression vs when you run the regression with the original child_scst variable?
- This regression estimate of the treatment effect is biased, whereas the regression with the original child_scst variable was accurate
- This regression estimates the treatment effect correctly, whereas the regression with the original child_scst variable was biased
- This regression has more observations than the regression with the original child_scst variable
- This regression has fewer observations than the regression with the original child_scst variable
- Random chance
- None of the above
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Data Analysis for Impact Evaluations – Quiz 2

Quiz Summary

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Results

Results

Categories

1. Question

2. Question

Regress total Year 3 endline scores on treatment. Then regress total Year 3 endline scores on treatment and child_female.

3. Question

4. Question

Repeat the regression in the video with child_scst as a control but without dropping observations that are missing values for child_scst.

5. Question

Providing evidence-based recommendations to improve Philippine education

Innovating for inclusive impact

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Using primary data to enhance public service delivery

Pushing the boundaries on evidence-based policy-making in West and North Africa

Investing in inclusive growth for Southeast Asia

2024 Dignity Report

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Quiz Summary

Information

Results

Results

Categories

1. Question

2. Question

Regress total Year 3 endline scores on treatment. Then regress total Year 3 endline scores on treatment and child_female.

3. Question

4. Question

Repeat the regression in the video with child_scst as a control but without dropping observations that are missing values for child_scst.

5. Question

Providing evidence-based recommendations to improve Philippine education

Innovating for inclusive impact

Why we invested in process improvement – and what we’ve gained thus far

Using primary data to enhance public service delivery

Pushing the boundaries on evidence-based policy-making in West and North Africa

Investing in inclusive growth for Southeast Asia

2024 Dignity Report

2024 Dignity Report

2024 Dignity Report

2024 Dignity Report

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