This page lists down a set of **30 interview questions on Logistic Regression (machine learning / data science)** in form of **objective questions** and also provides links to a set of three practice tests which would help you test / check your knowledge on ongoing basis. These questions and practice tests is intended to primarily help **interns / freshers / beginners** to help them brush up their knowledge in **logistic regression **from time-to-time. The following is a list of topics covered on this page.

- Introduction to logistic regression
- Logistic regression examples
- Evaluating performance of logistic regression and related techniques including AIC, deviance, ROC etc.
- Difference between linear and logistic regression

### Logistic Regression Practice Tests

This is a set of practice tests (**10 questions and answers each**) which can be taken to quickly check your concepts on logistic regression. The questions included in these practice tests are listed in later section.

- Logistic regression practice test – Set 1
- Logistic regression practice test – Set 2
- Logistic regression practice test – Set 3

### Logistic Regression Interview Question Set

- Logistic regression is used to predict _________ valued output?
- Continuous
- Categorical

- How much marks a strudent can get in a competitive exam based on hours of study can be solved using _________ regression model
- Multi-linear
- Logistic

- Logistic regression is _________ when the observed outcome of dependent variable can have only two values such as 0 and 1 or success and failure
- Binomial
- Multinomial
- Ordinal

- Whether a strudent will pass or fail in the competitive exam based on hours of study can be solved using _________ regression model
- Multi-linear
- Logistic

- ________ regression can be termed as a special case of _________ regression when the outcome variable is categorical
- Logistic, Linear
- Linear, Logistic

- In logistic regression, the goal is to predict _________
- Actual value of outcome dependent variable
- Odds of outcome dependent variable

- Which of the following can be used to evaluate the performance of logistic regression model?
- Adjusted R-Squared
- AIC

- Which of the following is link function in logistic regression
- Identity
- Logit

- Logistic regression is _________ when the observed outcome of dependent variable can have multiple possible types
- Binomial
- Multinomial
- Ordinal

- In logistic regression, following technique is used to measure the goodness of the fit
- Sum of squares calculations
- Deviance calculations

- Which of the following can be used to evaluate the performance of logistic regression model?
- AIC
- Null and Residual Deviance
- Both of the above
- None of the above

- Given two model with different AIC value, which one would be preferred model?
- One with higher AIC value
- One with lower AIC value

- Deviance is a measure of difference between a _______ model and the _________ model
- saturated, fitted
- Fitted, saturated

- Logistic regression is _________ when the observed outcome of dependent variable are ordered
- Binomial
- Multinomial
- Ordinal

- Logit transformation is log of ___________
- Odds of the event happening for different levels of each independent variable
- Ratio of odds of the event happening for different levels of each independent variable

- Logistic function is _________
- Dependent variable equalling a given case
- Probability that dependent variable equals a case

- Deviance is is a function of ________
- Exponential function of likelihood ratio
- Logrithmic function of likelihood ratio

- The odds of the dependent variable equaling a case (given some linear combination x of the predictors) is equivalent to _______
- Log function of the linear regression expression
- Exponential function of the linear regression function

- Regression coefficients in logistic regression are estimated using ________
- Ordinary least squares method
- Maximum likelihood estimation method

- _________ is analogous to __________ in linear regression
- Sum of squares calculations, deviance
- Deviance, sum of squares calculations

- Deviance can be shown to follow __________
- t-distribution
- F-distribution
- Chi-square distribution
- None of the above

- ______ value of deviance represents the better fit of model
- Higher
- Lower

- If the model deviance is significantly ________ than the null deviance then one can conclude that the predictor or set of predictors significantly improved model fit
- Smaller
- Larger

- Which of the following is analogous to R-Squared for logistic regression
- Likelihood ration R-squared
- McFadden R-squared
- Cox and Snell R-Squared
- All of the above

- Estimation in logistic regression chooses the parameters that ___________ the likelihood of observing the sample values
- Minimizes
- Maximizes

- Which of the following tests can be used to assess whether the logistic regression model is well calibrated
- Hosmer-Lemeshow test
- ROC Curve
- Both of the above

- ROC related with ROC curve stands for _______
- Regression Optimization Characteristic
- Regression Operating Characteristic
- Receiver Operating Characteristic

- Which of the following is used to identify the best threshold for separating positive and negative classes
- Hosmer-Lemeshow test
- ROC Curve
- Both of the above

- ROC curve is a plot of __________ vs ___________
- Sensitivity, 1-specificity
- 1-specificity, Sensitivity

- ______ the value of AUC, better is the prediction power of the model
- Lower
- Higher

### Ajitesh Kumar

Ajitesh has been recently working in the area of AI and machine learning. Currently, his research area includes Safe & Quality AI. In addition, he is also passionate about various different technologies including programming languages such as Java/JEE, Javascript and technologies such as Blockchain, mobile computing, cloud-native technologies, application security, cloud computing platforms, big data etc.

He has also authored the book, Building Web Apps with Spring 5 and Angular.

He has also authored the book, Building Web Apps with Spring 5 and Angular.

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