Data science is an emerging career field which has a huge number of jobs for the interesting candidates. We have already told you about the data science job requirements by the industries as well top data science training courses to become skilled data professionals. So, now today we are going to discuss one of the most important aspects of getting a job. In interviews, two things matter most first your body language and second is your knowledge of the field. We are going to list top10 **data science interview questions** that you might get in your data science interview.

The questions will help you to analyse yourself and about your preparation that you have done for the interview. If you are able to answer all the below questions then you are good to go for the interview. But if you are not confident enough to answer any of the questions then you should prepare once again. As cracking interview will be your last step towards entering in data science world and work. Let’s discuss the** data science interview questions and answers**.

## Top 10 Data Analyst Interview Questions with answers

Frankly, speaking data science is not an easy field to enter. And with this, almost all data scientists will also agree. Apart from learning the subjects, data scientists also are provided with an intense training program to acquire the skills. With all the requirements like training, certifications one should also have knowledge of **data analytics interview questions**.

- How would you create a taxonomy to identify key customer trends in unstructured data?

The best way to approach and answer this question is first to mention that it is best to check with the business owner as well as understand their objectives before categorising all the data. It is always a good way to follow the iterative approach. This ensures that your model you created is producing actionable results and is also improving over the time.

2. Python or R – Which one would you prefer for the text analytics?

The best answer that you can give for this question is Python because it has Pandas library which provides easy to use data structures and also high-performance data analyst tools.

3. Which technique is used to predict categorical responses?

To predict the categorical responses classification technique that is widely used in mining for classifying the data sets.

4. What is logistic regression?

Logistic Regression is also referred as logit model. It is a technique which is used to predict the binary outcome from a linear combination of the predictor variables.

5. What are Recommender Systems?

A recommender system is a subclass of information filtering systems which are used to predict the preferences and ratings that a user would according to their views to the product. Recommender systems are widely used in movies, news, research articles, products, social tags, music, etc.

6. Differentiate between univariate, bivariate and multivariate analysis.

All of the above univariates, bivariate and multivariate are the descriptive statistical analysis techniques that can be easily differentiated based on the number of variables that are involved at a given point of time.

7. What do you understand by the term Normal Distribution?

Data is distributed in many different ways with a bias to the right, left or it can all be jumbled up. However, there also chances of the data to be distributed around the central value without being bias to right or left and it reaches to the value of normal distribution having a bell shape. All the unknown or random variables are distributed in the form that makes a shape of a symmetrically shaped bell.

8. What do you mean by Linear Regression?

Linear regression is a statistical technique in which the score of a variable X can be predicted from the score of a second variable Y. Y is referred as the predictor variable and X is referred as the criterion variable.

9. What are the Interpolation and Extrapolation?

The method of estimating a value from the two unknown values from a list of values is known as the Interpolation. Extrapolation is approximating a value by extending a known set of values or facts.

10. What does P-value signify about the statistical data?

In statistical data, P-value is used to determine the significance of results after the hypothesis test . P-value helps the readers to get the conclusions and the value is always between 0 and 1 not more than that. Different values have their different significance as given below.

- P- Value > 0.05: It denotes the weak evidence against the null hypothesis that means null hypothesis cannot be rejected.
- P-value <= 0.05: It denotes the strong evidence against the null hypothesis that means null hypothesis can be rejected.
- P-value=0.05: It is the marginal value that indicates it is possible to go either way.

So here end the ten **data analyst interview question and answers**. These questions will help you to get an idea that what type of questions is asked in the interviews. This doesn’t mean that these questions will definitely be in an interview but they might be,=. The questions are just to give you a sight of interview questions If you have any query regarding the questions, answers or the post then leave a comment below we will reply you at the earliest.

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