Research Analyst Intern

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Research Analyst Intern Interview Questions and Answers

Updated 3 Apr 2024

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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

Q2. Explain about extrusion technology

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

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Q3. Explain basic regression

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.

Q4. Describe basic 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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Q5. Explain a p value

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

Research Analyst Intern Jobs

Research Analyst Intern 0-1 years
Qubit Capital
5.0
Remote
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