Preview Questions Data Analyst | Role Specific Skill

Question 1: How can you handle currency conversion when generating a report that compares transactions in different currencies for a financial institution?

Which action should you take?

Choose only one option

Use a fixed exchange rate for all transactions

Normalize all data to USD

Apply conversion rates to each transaction

Ignore currency differences

Question 2: Which of the following is a key assumption of linear regression that must be checked to ensure the validity of the model in credit risk analysis?

Which action should you take?

Choose only one option

The dependent variable is categorical

The residuals are normally distributed

The model includes all possible interaction terms

There is no relationship between the independent variables and the dependent variable

Question 3: In the context of BFSI, which statistical test is most appropriate for comparing the means of loan approval rates between two different branches of a bank?

Which action should you take?

Choose only one option

ANOVA

Independent Samples t-Test

Chi-Square Test

Mann-Whitney U Test

Question 4: Which of the following techniques is used to handle missing data in a dataset where values are missing randomly and not systematically?

Which action should you take?

Choose only one option

Fill missing values with a constant

Use multiple imputation methods

Drop rows with missing values

Impute missing values using the mean

Question 5: How should a data analyst handle categorical variables in a financial dataset with many unique categories (e.g., account types)?

Which action should you take?

Choose only one option

Ignore the categorical variables

Replace each category with its numerical index

Use one-hot encoding for each unique category

Group the categories into broader classes

Question 6: In financial risk modeling, how would you assess the relationship between two non-linear variables, such as stock returns and economic indicators?

Which action should you take?

Choose only one option

Use Spearman's rank correlation

Perform a non-linear regression

Apply a chi-square test

Use Pearson's correlation coefficient