# Regression Analysis MCQs Solution | TCS Fresco Play

**Disclaimer: The primary purpose of providing this solution is to assist and support anyone who are unable to complete these courses due to a technical issue or a lack of expertise. This website's information or data are solely for the purpose of knowledge and education.**

**Make an effort to understand these solutions and apply them to your Hands-On difficulties. (It is not advisable that copy and paste these solutions).**

**All Question of the MCQs Present Below for Ease Use Ctrl + F with the question name to find the Question. All the Best!**

1. What is the value of the estimated coef for variable RM ?

**9.1021 -- Correct**

2. What is the value of the constant term ?

**-34.6706 -- Correct**

3. What is the adjusted R sq value ?

**0.483 -- Correct**

4. What is the value of R sq ?

**0.484 -- Correct**

5. How many observations are there in the dataset ?

**506 -- Correct**

**************************

6. Perform a correlation among all the independent variables . What is the correlation between variables NOX and DIS ?

**-0.76923 -- Correct**

7. What is the P>|t| value for the 'INDUS' variable ?

**0.731 -- Correct**

8. What is the standard error for the constant term ?

**5.104 -- Correct**

9. What is the value of the estimated coef for the constant term ?

**36.4911 -- Correct**

10. what is the value of R sq ?

**0.741 -- Correct**

****************************

11. Regression can show causal relationship between two variables.

**False -- Correct**

12. In Multi Variable regression you predict one variable using more than one variable

**True -- Correct**

13. The SSE depends on the number of observations in the data set

**True -- Correct**

14. __________ means predicting one variable from another.

**Regress -- Correct**

15. What is the process of removing the mean and dividing the value by the standard deviation

**Standatdization -- Correct**

16. __________ is a unit less quantity

**R Square -- Correct**

17. When two or more variables are correlated in a Multiple Regression Model , it is called as ____________

**Multi Collinearity -- Correct**

18. What is the process of rescaling the values in the range [0,1]

**Normalization -- Correct**

19. What is the formula for root means square error ?

**sqrt(SSE/n) -- Correct**

20. It is advised to omit a term that is highly correlated with another while fitting a Multiple Regression Model

**True -- Correct**

21. When more variables are added in Multi Variable Regression the marginal improvement decreases as each variable is added. This term is called ?

**Law of Diminishing Returns -- Correct**

22. R Square Value can be greater than zero

**False -- Correct**

23. Arithmetic Mean can be used as a prediction measure.

**True -- Correct**

24. What is the sum of standard error for the baseline model ?

**SST -- Correct**

25. SSE is _________ for the Line of Best Fit and _______ for the baseline model

**Small , Big -- Correct**

26. It is advised to go for a simpler model while fitting multiple regression for a dataset

**True -- Correct**

27. What is the term that represents the difference between actual and predicted value called ?

**Residual -- Correct**

28. What is the basic property of the model of best fit ?

**Minimize Error -- Correct**

29. By adding multiple variables in Multi Variable Regression , the model accuracy _____________

**Increases -- Correct**

30. Sum of Squared error is a measure of standard for a Regression Line

**True -- Correct**

31. What is the good range of correlation values to include in the regression model

**-0.7 to + 0.7 -- Correct**

32. What is the quantity that measures the strength of relationship between two variables ?

**Correlation -- Correct**

33. pr(>|t|) term signifies how likely the estimated value is zero

**True -- Correct**

34. It is OK to discard theoretical considerations for Statistical Measures

**False -- Correct**

If you have any queries, please feel free to ask on the comment section.If you want MCQs and Hands-On solutions for any courses, Please feel free to ask on the comment section too.Please share and support our page!

## Post a Comment