Rudhra Info Solutions Interview Questions and Answers

Standard deviation is a measure of the amount of variation or dispersion of a set of values.

• Standard deviation is calculated as the square root of the variance.

• It measures how spread out the values in a data set are around the mean.

• A higher standard deviation indicates more variability in the data.

• Formula for standard deviation: sqrt(Σ(x - μ)² / N), where x is each value, μ is the mean, and N is the number of values.

Correlation measures the relationship between two variables, regression predicts a dependent variable based on independent variables, and gradient descent is an optimization algorithm for finding the minimum of a function.

• Correlation measures the strength and direction of a linear relationship between two variables. It ranges from -1 to 1.

• Regression is a statistical technique used to model the relationship between a dependent variable and one or more independent variables. It...read more

I will select columns based on relevance to the analysis goals and data quality.

• Identify columns relevant to the analysis goals

• Consider data quality and completeness of each column

• Remove redundant or irrelevant columns

• Use statistical methods or domain knowledge to prioritize columns

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

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

• A higher R square value indicates that the model explains a larger proportion of the variance in the dependent variable.

Probability and distributions, linear regression definition and explanation

• Probability and distributions involve analyzing the likelihood of different outcomes occurring

• Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables

• It aims to find the best-fitting line that represents the relationship between the variables

• The line is determined by minimizing the sum of the squared differences between ...read more

Assumptions of linear regression 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.

• No multicollinearity: The independent variables are not highly correlated with ea...read more

The Black Scholes equation is a mathematical model used to calculate the theoretical price of European-style options.

• The equation is used to determine the price of a call or put option over time.

• It takes into account factors such as the current stock price, strike price, time to expiration, risk-free interest rate, and volatility.

• The formula is: C = S*N(d1) - X*e^(-rt)*N(d2) for a call option, and P = X*e^(-rt)*N(-d2) - S*N(-d1) for a put option.

• Where C is the call option pri...read more