ECON 1117
Data Analysis & Econometrics — Practice Question Bank
150+ Problems with Fully Worked Solutions
Independent Study Resource
Not affiliated with or endorsed by Yale University
Based on OpenStax Introductory Statistics 2e (CC BY 4.0) and original econometrics content
Edition 2026
Explore our developer-friendly HTML to PDF API Printed using PDFCrowd HTML to PDF
,Table of Contents
1. How to Use This Question Bank
2. Chapter 1: From Economic Question to Data — 10 problems
3. Chapter 2: Data Quality, Sampling, and Measurement — 10 problems
4. Chapter 3: Probability Foundations — 12 problems
5. Chapter 4: Descriptive Statistics — 12 problems
6. Chapter 5: Sampling Distributions and Inference — 10 problems
7. Chapter 6: Hypothesis Testing and P-Values — 12 problems
8. Chapter 7: Confidence Intervals — 10 problems
9. Chapter 8: Selection, Causation, and Counterfactuals — 10 problems
10. Chapter 9: Regression Foundations — 12 problems
11. Chapter 10: Model Specification and Interpretation — 10 problems
12. Chapter 11: Multiple Regression and Controls — 10 problems
13. Chapter 12: Causal Inference in Practice — 12 problems
14. Chapter 13: Machine Learning and Big Data — 10 problems
15. Chapter 14: Empirical Research and Ethics — 8 problems
16. Final Mixed Practice Exam — 25 problems
17. Full Answer Key with Worked Solutions
18. Quick Formula Reference
Explore our developer-friendly HTML to PDF API Printed using PDFCrowd HTML to PDF
,How to Use This Question Bank
This question bank complements the ECON 1117 Complete Study Guide. Where the guide teaches the
concepts, this bank trains you to apply them under exam conditions.
Recommended workflow
1. Attempt each problem without looking at the solution. Set a timer: 3–5 minutes per
computational problem, 6–10 minutes for applied or conceptual problems.
2. Check your method, not just your answer. Every solution explains the reasoning — compare
against it.
3. Re-do missed problems after 48 hours. Spaced repetition is the strongest retention tool.
4. Use the final mixed exam last. It integrates everything under a single time limit.
Difficulty Legend
[C] Computational — apply a formula directly.
[A] Applied — translate a real economic scenario into an empirical framework.
[X] Conceptual — test understanding of the underlying reasoning.
[★] Challenge — exam-level, multi-step problems.
Explore our developer-friendly HTML to PDF API Printed using PDFCrowd HTML to PDF
, Chapter 1 — From Economic Question to Data
Problems
1.1 [X] Classify each question as descriptive, predictive, or causal: (a) How has the unemployment rate
changed since 2010? (b) What predicts whether a student graduates? (c) Does a higher minimum wage
reduce employment?
1.2 [X] Define the unit of analysis for a study of state-level environmental policy.
1.3 [C] A dataset has 500 observations with 6 variables. How many cells does the dataset contain?
1.4 [X] Explain why the type of question (descriptive, predictive, causal) determines the empirical
method.
1.5 [A] A researcher wants to estimate the effect of education on wages. What is the outcome variable,
the treatment variable, and the unit of analysis?
1.6 [X] What is the difference between a hypothesis and a research question?
1.7 [C] A study compares test scores across 30 schools. What is the population if the researcher wants
to generalize to all schools in the United States?
1.8 [A] A company wants to know whether a new ad campaign increases sales. What type of empirical
question is this?
1.9 [★] You are asked to study whether remote work affects productivity. Write one descriptive, one
predictive, and one causal question about this topic.
1.10 [★] Explain why a "causal" question cannot be answered with observational data without an
identification strategy.
Worked Solutions
1.1 (a) Descriptive, (b) Predictive, (c) Causal.
1.2 The state (each observation is a state-year or state).
1.3 500 × 6 = 3,000 cells.
1.4 Causal questions require identification (randomization, IV, DiD, RDD); descriptive questions require
representative measurement; predictive questions prioritize out-of-sample accuracy.
1.5 Outcome: wage. Treatment: education level. Unit: individual worker.
Explore our developer-friendly HTML to PDF API Printed using PDFCrowd HTML to PDF
Data Analysis & Econometrics — Practice Question Bank
150+ Problems with Fully Worked Solutions
Independent Study Resource
Not affiliated with or endorsed by Yale University
Based on OpenStax Introductory Statistics 2e (CC BY 4.0) and original econometrics content
Edition 2026
Explore our developer-friendly HTML to PDF API Printed using PDFCrowd HTML to PDF
,Table of Contents
1. How to Use This Question Bank
2. Chapter 1: From Economic Question to Data — 10 problems
3. Chapter 2: Data Quality, Sampling, and Measurement — 10 problems
4. Chapter 3: Probability Foundations — 12 problems
5. Chapter 4: Descriptive Statistics — 12 problems
6. Chapter 5: Sampling Distributions and Inference — 10 problems
7. Chapter 6: Hypothesis Testing and P-Values — 12 problems
8. Chapter 7: Confidence Intervals — 10 problems
9. Chapter 8: Selection, Causation, and Counterfactuals — 10 problems
10. Chapter 9: Regression Foundations — 12 problems
11. Chapter 10: Model Specification and Interpretation — 10 problems
12. Chapter 11: Multiple Regression and Controls — 10 problems
13. Chapter 12: Causal Inference in Practice — 12 problems
14. Chapter 13: Machine Learning and Big Data — 10 problems
15. Chapter 14: Empirical Research and Ethics — 8 problems
16. Final Mixed Practice Exam — 25 problems
17. Full Answer Key with Worked Solutions
18. Quick Formula Reference
Explore our developer-friendly HTML to PDF API Printed using PDFCrowd HTML to PDF
,How to Use This Question Bank
This question bank complements the ECON 1117 Complete Study Guide. Where the guide teaches the
concepts, this bank trains you to apply them under exam conditions.
Recommended workflow
1. Attempt each problem without looking at the solution. Set a timer: 3–5 minutes per
computational problem, 6–10 minutes for applied or conceptual problems.
2. Check your method, not just your answer. Every solution explains the reasoning — compare
against it.
3. Re-do missed problems after 48 hours. Spaced repetition is the strongest retention tool.
4. Use the final mixed exam last. It integrates everything under a single time limit.
Difficulty Legend
[C] Computational — apply a formula directly.
[A] Applied — translate a real economic scenario into an empirical framework.
[X] Conceptual — test understanding of the underlying reasoning.
[★] Challenge — exam-level, multi-step problems.
Explore our developer-friendly HTML to PDF API Printed using PDFCrowd HTML to PDF
, Chapter 1 — From Economic Question to Data
Problems
1.1 [X] Classify each question as descriptive, predictive, or causal: (a) How has the unemployment rate
changed since 2010? (b) What predicts whether a student graduates? (c) Does a higher minimum wage
reduce employment?
1.2 [X] Define the unit of analysis for a study of state-level environmental policy.
1.3 [C] A dataset has 500 observations with 6 variables. How many cells does the dataset contain?
1.4 [X] Explain why the type of question (descriptive, predictive, causal) determines the empirical
method.
1.5 [A] A researcher wants to estimate the effect of education on wages. What is the outcome variable,
the treatment variable, and the unit of analysis?
1.6 [X] What is the difference between a hypothesis and a research question?
1.7 [C] A study compares test scores across 30 schools. What is the population if the researcher wants
to generalize to all schools in the United States?
1.8 [A] A company wants to know whether a new ad campaign increases sales. What type of empirical
question is this?
1.9 [★] You are asked to study whether remote work affects productivity. Write one descriptive, one
predictive, and one causal question about this topic.
1.10 [★] Explain why a "causal" question cannot be answered with observational data without an
identification strategy.
Worked Solutions
1.1 (a) Descriptive, (b) Predictive, (c) Causal.
1.2 The state (each observation is a state-year or state).
1.3 500 × 6 = 3,000 cells.
1.4 Causal questions require identification (randomization, IV, DiD, RDD); descriptive questions require
representative measurement; predictive questions prioritize out-of-sample accuracy.
1.5 Outcome: wage. Treatment: education level. Unit: individual worker.
Explore our developer-friendly HTML to PDF API Printed using PDFCrowd HTML to PDF
