/  Regression-Quiz-1

This Quiz contains totally 10 Questions each carry 1 point for you.

1. Which of the following step/assumption in regression modeling impacts the trade-off between under-fitting and over-fitting the most.

The Polynomial degree
Whether we learn the weights by matrix inversion or gradient
Use of a constant-term

Correct!

Wrong!

2. Suppose you have the following data with one real-value input variable & one real-value output variable. What is leave-one out cross validation mean square error in case of linear regression (Y = bX+c)?


10/27
20/27
50/27
49/27

Correct!

Wrong!

3. Which of the following is/ are true about “Maximum Likelihood estimate (MLE)”?
1. MLE may not always exist
2. MLE always exists
3. If MLE exist, it (they) may not be unique
4. If MLE exist, it (they) must be unique

1 and 4
2 and 3
1 and 3
2 and 4

Correct!

Wrong!

4. Let’s say, a “Linear regression” model perfectly fits the training data (train error is zero). Now, Which of the following statement is true?

You will always have test error zero
You cannot have test error zero 
None of the above
All of the above

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Wrong!

5. In a linear regression problem, we are using “R-squared” to measure goodness-of-fit. We add a feature in linear regression model and retrain the same model. Which of the following option is true?

If R Squared increases, this variable is significant
If R Squared decreases, this variable is not significant.
Individually R squared cannot tell about variable importance. We can’t say anything about it right now.
None of these

Correct!

Wrong!

6. Which one of the statement is true regarding residuals in regression analysis?

Mean of residuals is always zero
Mean of residuals is always less than zero
Mean of residuals is always greater than zero
There is no such rule for residuals.

Correct!

Wrong!

7. Which of the one is true about Heteroskedasticity?

Linear Regression with varying error terms
Linear Regression with constant error terms
Linear Regression with zero error terms
None of these

Correct!

Wrong!

8. Which of the following indicates a fairly strong relationship between X and Y?

Correlation coefficient = 0.9
The p-value for the null hypothesis Beta coefficient =0 is 0.0001
The t-statistic for the null hypothesis Beta coefficient=0 is 30
None of these

Correct!

Wrong!

9. 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.

1,2 and 3
1,3 and 4
1 and 3
All of the above

Correct!

Wrong!

10. To test linear relationship of y(dependent) and x(independent) continuous variables, which of the following plot best suited?

Scatter plot
Bar chart
Histograms
None of these

Correct!

Wrong!

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Regression Models – Quiz1

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