Research Analyst Intern

Research Analyst Intern Interview Questions and Answers

Updated 3 Apr 2024

Q1. Describe a problem you encountered when performing your analysis and how you resolved it

Ans.

Encountered a data discrepancy while analyzing sales data

Discovered inconsistencies in sales figures between different data sources
Investigated the issue by cross-referencing data and identifying the source of the discrepancy
Resolved the problem by updating the incorrect data and ensuring consistency across all sources

Ans.

Extrusion technology is a manufacturing process that involves forcing material through a die to create a specific shape or form.

Extrusion is commonly used in the production of plastic products such as pipes, tubing, and sheets.
The process involves heating the material to a specific temperature and then forcing it through a die using a screw or piston.
Extrusion can also be used to create metal products such as rods, wires, and tubes.
The technology is widely used in various ind...read more

Research Analyst Intern Interview Questions and Answers for Freshers

Ans.

Basic regression is a statistical method used to analyze the relationship between a dependent variable and one or more independent variables.

Regression helps in predicting the value of the dependent variable based on the values of independent variables.
It is used to understand the strength and direction of the relationship between variables.
Common types of regression include linear regression, logistic regression, and polynomial regression.

Ans.

Basic regression is a statistical method used to analyze the relationship between a dependent variable and one or more independent variables.

Regression analysis is used to predict the value of the dependent variable based on the values of the independent variables.
The most common type of regression is linear regression, where a straight line is used to model the relationship between variables.
Other types of regression include logistic regression for binary outcomes and polyno...read more

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Ans.

A p value is a measure of the strength of evidence against the null hypothesis in a statistical hypothesis test.

P value is a probability value that measures the likelihood of obtaining results at least as extreme as the observed results, assuming the null hypothesis is true.
A p value less than 0.05 is typically considered statistically significant, indicating strong evidence against the null hypothesis.
A p value greater than 0.05 suggests that the results are not statisticall...read more