Q.No.1. The _________ metric measures the squared difference between predicted and actualvalues in linear regression

Question 9In Linear Regression, which statement is correct about Sum Squared Error?1 pointThe Sum Squared Error measures the distance between the truth and predicted values.The Sum Squared Error measures the distance between the truth and the average values of the truth.The Sum Squared Error is a measure of the explained variation of our model.The Sum Squared Error measures the distance between the predicted values and the average values of the truth.

7. Which among the following is a metric to measure a regression problem which has a characteristic of penalising large losses more than small losses?- i. mean squared error- ii. mean absolute error- iii. mean absolute percentage error- iv. accruracyi. onlyii. and iii. onlyiv. onlyall of the mentionediii. onlyii. only

2. Discuss Linear Regression with an example.

Question 1: In a regression analysis, what information gives R²?a) The unexplained variance by the predictorsb) The share of the dependent variable variance explained by the predictorsc) The badness of the fitd) The quality of the data selection

Which two of the of the following statements are correct regarding R2 as a tool to evaluate a regression model. Multiple answers allowed.a.The R2 is the proportion of the total variation in X that can be explained by the variation in the dependent variable in the model.b. If the R2 value is greater than 1, then it shows that the regression model is a very good fit.c.The R2 value needs to be reported in presenting regression results as it shows the relative precision of the model for the users to consider.d.R2 reflects the model’s improvement of the predicted value over the estimator of the sample mean (Y-bar).