Which of the following option is true regarding Regression and Correlation ?Note: y is dependent variable and x is independent variable.

Related MCQs

• Which of the following option is true regarding �Regression� and �Correlation� ?Note: y is dependent variable and x is independent variable.
• Which of the following option is true regarding “Regression” and “Correlation” ?Note: y is dependent variable and x is independent variable.
• Suppose that we have N independent variables (X1,X2� Xn) and dependent variable is Y. Now Imagine that you are applying linear regression by fitting the best fit line using least square error on this data. You found that correlation coefficient for one of it�s variable(Say X1) with Y is -0.95.Which of the following is true for X1?
• Suppose that we have N independent variables (X1,X2… Xn) and dependent variable is Y. Now Imagine that you are applying linear regression by fitting the best fit line using least square error on this data. You found that correlation coefficient for one of it’s variable(Say X1) with Y is -0.95.Which of the following is true for X1?
• Suppose that we have N independent variables (X1,X2… Xn) and dependent variable is Y. Now Imagine that you are applying linear regression by fitting the best fit line using least square error on this data. You found that correlation coefficient for one of it’s variable(Say X1) with Y is 0.95.
• A regression model in which more than one independent variable is used to predict the dependent variable is called
• Which of the following assumptions do we make while deriving linear regression parameters? 1. The true relationship between dependent y and predictor x is linear 2. The model errors are statistically independent 3. The errors are normally distributed with a 0 mean and constant standard deviation 4. The predictor x is non-stochastic and is measured error-free
• In a simple linear regression model (One independent variable), If we change the input variable by 1 unit. How much output variable will change?
• In a simple linear regression model (One independent variable), If we change the input variable by 1 unit. How much output variable will change?
• What is/are true about ridge regression? 1. When lambda is 0, model works like linear regression model 2. When lambda is 0, model doesn't work like linear regression model 3. When lambda goes to infinity, we get very, very small coefficients approaching 0 4. When lambda goes to infinity, we get very, very large coefficients approaching infinity