1. What is the sum of standard error for the baseline model?
View Answer
SST
2. __________ means predicting one variable from another.
View Answer
Regress
3. R Square Value can be greater than zero.
View Answer
False
4. ________ is a unit less quantity.
View Answer
R Square
5. Two or more variables correlating in a Multiple Regression Model is known as ____________.
View Answer
Multi–Correlation
6. It is recommended to exclude a term that is deeply correlated with another while fitting a Multiple Regression Model.
View Answer
True
7. Regression exhibits a causal relationship between two variables.
View Answer
False
8. The SSE is based on the number of observations present in the data set.
View Answer
True
9. SSE is _________ for the Line of Best Fit and _______ for the baseline model.
View Answer
small,big
10. The process of eliminating the mean and then dividing the value by the standard deviation is called ____________.
View Answer
Normalization
11. Sum of Squared error is a measure of standard for a Regression Line.
View Answer
True
12. Discarding theoretical considerations for Statistical Measures is OK.
View Answer
False
13. Arithmetic Mean can be used as a prediction measure.
View Answer
True
14. What is the quantity that measures the strength of the relationship between two variables?
View Answer
Corr
15. The formula for root means square error is _____________.
View Answer
sqrt(SSE/n)
16. It is advised to go for a simpler model while fitting multiple regression for a dataset.
View Answer
True
17. When more variables are included in Multi-Variable Regression, the marginal improvement drops as each variable is included. This term is known as _____________
View Answer
Law of Diminishing Returns
18. What is the basic property of the model of the best fit?
View Answer
Minimize Error
19. What is the term that represents the difference between actual and predicted value called?
View Answer
Residual
20. pr(>|t|) term signifies how likely the estimated value is zero.
View Answer
True
21. The process of rescaling the values in the range [0,1] is called __________.
View Answer
Normalization
22. What is the good range of correlation values to include in the regression model?
View Answer
-0.7 to + 0.7
23. In multivariable regression, you can predict a variable using more than one variable.
View Answer
True
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