Econometrics

The economtrics test is a multi choice test that measures the candidate’s knowledge of statistical concepts, exploratory analysis and statistical testing required to analyze economic data. 

Potential job titles that use the Econometrics solution include: Economist, Financial Quantitative Analyst, Economic Consultant, Revenue Research Analyst

What It’s Best Used For

• Vetting Quantitative and Finance Roles: Screening incoming applicants or reviewing current employees for advanced analytical positions like Economists, Financial Quantitative Analysts, Economic Consultants, and Revenue Research Analysts.
• Rapid Applicant Pre-Screening: Filtering down deep candidate pools early in the recruitment pipeline using a highly condensed, 12-question format that respects the applicant’s time.
• Auditing Data Modeling Capabilities: Evaluating an applicant’s technical understanding of simple linear regression, multivariable regression models, and core extensions of two-variable modeling frameworks.
• Verifying Statistical Testing Knowledge: Benchmarking a candidate’s grasp of foundational statistical hypothesis testing, including formulating null and alternate hypotheses, tracking Type I and Type II errors, and interpreting p-values or z-tests/t-tests.
• Flagging Data Violation Risks: Checking whether an analyst can successfully detect critical data-degrading factors like heteroscedasticity, specification bias, multicollinearity, and autocorrelation.
• Unproctored Remote Recruitment: Administering secure, web-based evaluations to remote or work-from-home candidates without needing a physical testing supervisor.

Job levels – Mid-Professional, Professional Individual Contributor, Graduate,
Language – English (USA),
Average Testing Time (minutes) – 11 minutes
Allowed Time: 20 minutes
Maximum Number of Questions – 12 questions
Designed for Unproctored Environment – Yes
Test Type – Multiple Choice
Sector: Business

Econometrics Scores Reported

• Overall Score
• Simple Linear Regression
• Multiple Linear Regression
• Violations of Classical Assumptions

Knowledge, Skills, Abilities and Competencies Measured

• Correlation and regression
• Formulating null & alternate hypothesis
• Type I and Type II errors
• Statistical tests (z-test/t-test) and p-value
• Multi-variate analysis and confidence intervals
• F-test & ANOVA
• Chi-square distribution
• Multivariable regression
• Extension of two variable model
• Heteroscedasticity, Specification bias and Multicollinearity
• Two variable hypothesis and two variable hypothesis testing
• Autocorrelation