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Biological E Interview Questions and Answers

Updated 18 Jun 2024

Q1. What do you know about R square?

Ans.

R square is a statistical measure that represents the proportion of the variance for a dependent variable that's explained by an independent variable.

  • R square is also known as the coefficient of determination.

  • It ranges from 0 to 1, with 1 indicating a perfect fit.

  • It is used to evaluate the goodness of fit of a regression model.

  • Higher R square values indicate that the model explains a larger proportion of the variance in the dependent variable.

  • For example, an R square of 0.8 m...read more

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Q2. Can R sq be negative?

Ans.

No, R sq cannot be negative as it represents the proportion of the variance in the dependent variable that is predictable from the independent variable.

  • R sq (R-squared) ranges from 0 to 1, where 0 indicates that the model does not explain any of the variability of the response data around its mean, and 1 indicates that the model explains all the variability.

  • A negative R sq value would imply that the model is worse at predicting the dependent variable than a model that simply ...read more

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Q3. How do you check the model fit

Ans.

Model fit can be checked using various statistical measures and techniques.

  • Check goodness of fit statistics like R-squared, AIC, BIC

  • Analyze residuals to ensure they are normally distributed and homoscedastic

  • Use diagnostic plots like QQ plots, residual plots, and leverage plots

  • Perform cross-validation to assess model performance on unseen data

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Q4. describe the regression process

Ans.

Regression process involves fitting a mathematical model to data points to predict outcomes.

  • Identify the relationship between the independent and dependent variables

  • Choose the appropriate regression model (linear, logistic, etc.)

  • Collect and preprocess data

  • Split data into training and testing sets

  • Fit the regression model to the training data

  • Evaluate the model using metrics like R-squared, Mean Squared Error, etc.

  • Use the model to make predictions on new data

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Q5. React advantages

Ans.

React is a popular JavaScript library for building user interfaces.

  • Component-based architecture for reusability and organization

  • Virtual DOM for efficient updates and performance

  • One-way data binding for predictable data flow

  • Support for server-side rendering for SEO optimization

  • Large community and ecosystem for support and resources

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Q6. Diffing algorithm

Ans.

A diffing algorithm is used to compare two sets of data and identify the differences between them.

  • Diffing algorithms are commonly used in version control systems to track changes in code.

  • Some popular algorithms for diffing include Myers' diff algorithm and the Hunt-McIlroy algorithm.

  • Diffing algorithms can be implemented using dynamic programming or other techniques to efficiently compare large datasets.

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