Filter interviews by
I applied via Referral and was interviewed before Jul 2023. There were 3 interview rounds.
30 general aptitude question and one email writing
Python numpy and pandas
Developed a survey programming tool to streamline data collection process.
Created user-friendly interface for survey creation
Implemented logic for skip patterns and branching
Integrated with data analysis software for seamless data transfer
I applied via Referral and was interviewed before Feb 2023. There were 2 interview rounds.
Linear regression assumptions include linearity, independence, homoscedasticity, and normality.
Linearity: The relationship between the independent and dependent variables is linear.
Independence: The residuals are independent of each other.
Homoscedasticity: The variance of the residuals is constant across all levels of the independent variables.
Normality: The residuals are normally distributed.
Example: If we are predict...
Multicollinearity is a phenomenon in which two or more predictor variables in a regression model are highly correlated.
Multicollinearity can lead to unstable estimates of the coefficients and make it difficult to determine the effect of each predictor variable on the outcome.
One way to tackle multicollinearity is to identify the highly correlated variables and consider removing one of them from the model.
Another approa...
Time series analysis components include trend, seasonality, cyclicality, and irregularity.
Trend: Long-term movement or direction of the data.
Seasonality: Regular patterns that occur at specific intervals.
Cyclicality: Repeating patterns that are not necessarily at fixed intervals.
Irregularity: Random fluctuations or noise in the data.
Examples: Trend in stock prices, seasonality in retail sales, cyclicality in economic c
Preventive measures for regression assumptions not met
Check for multicollinearity among independent variables
Transform variables if they are not normally distributed
Consider using non-parametric regression methods
Use robust regression techniques to handle outliers
Collect more data to improve model performance
Handling missing values is crucial in data analysis. Various techniques like imputation, deletion, or prediction can be used.
Use imputation techniques like mean, median, mode to fill in missing values.
Consider using predictive modeling to estimate missing values based on other variables.
Delete rows or columns with a high percentage of missing values if they cannot be accurately imputed.
Use advanced techniques like K-ne...
Tuple is immutable and fixed in size, while list is mutable and can change in size.
Tuple is created using parentheses, while list is created using square brackets.
Tuple elements can be of different data types, while list elements are usually of the same data type.
Tuple is faster than list for iteration and accessing elements.
Example: tuple = (1, 'a', True), list = [1, 2, 3]
Outliers can be detected using statistical methods like Z-score, IQR, or visualization techniques like box plots.
Calculate Z-score for each data point and identify points with Z-score greater than a certain threshold (usually 3 or -3).
Use Interquartile Range (IQR) to identify outliers by determining data points that fall below Q1 - 1.5 * IQR or above Q3 + 1.5 * IQR.
Visualize the data using box plots and identify points...
I applied via Approached by Company and was interviewed in Jan 2022. There were 2 interview rounds.
I applied via LinkedIn and was interviewed before Mar 2023. There were 3 interview rounds.
Written test covering economic questions
Ipsos interview questions for popular designations
I applied via campus placement at Calcutta University and was interviewed before Apr 2023. There was 1 interview round.
Regression is a statistical technique used to understand the relationship between a dependent variable and one or more independent variables. Multicollinearity occurs when independent variables in a regression model are highly correlated.
Regression helps in predicting the value of the dependent variable based on the values of independent variables.
Multicollinearity can lead to issues in interpreting the coefficients of...
Get interview-ready with Top Ipsos Interview Questions
I applied via Naukri.com and was interviewed in Mar 2022. There were 2 interview rounds.
I applied via Recruitment Consulltant and was interviewed before Jan 2023. There were 3 interview rounds.
Html, javascript, css, sql MCQ from w3 school would be enough
Data structure:searching and sorting
I applied via Referral and was interviewed before Mar 2023. There was 1 interview round.
I applied via Recruitment Consulltant and was interviewed in Nov 2021. There was 1 interview round.
I applied via Company Website and was interviewed before Feb 2023. There were 3 interview rounds.
Why you , why the company, why this job
Writing test that was allowed to take home
Fit test with head of department
Top trending discussions
The duration of Ipsos interview process can vary, but typically it takes about less than 2 weeks to complete.
based on 44 interviews
Interview experience
Research Executive
155
salaries
| ₹5.9 L/yr - ₹11 L/yr |
Analyst
135
salaries
| ₹5.6 L/yr - ₹8.6 L/yr |
Senior Research Executive
114
salaries
| ₹8 L/yr - ₹13.5 L/yr |
Data Analyst
76
salaries
| ₹4 L/yr - ₹9 L/yr |
Research Manager
71
salaries
| ₹8.7 L/yr - ₹17.5 L/yr |
Nielsen Holdings
Kantar
GfK MODE
Market Xcel Data Matrix