Data Analyst Interview Questions

1. What are Support Vectors in SVM?

A Support Vector Machine (SVM) is an algorithm that tries to fit a line (or plane or hyperplane) between the different classes that maximizes the distance from the line to the points of the classes.
In this way, it tries to find a robust separation between the classes. The Support Vectors are the points of the edge of the dividing hyperplane.


2. Explain Correlation and Covariance?

Covariance signifies the direction of the linear relationship between two variables, whereas correlation indicates both the direction and strength of the linear relationship between variables.


3.What is the cluster sampling techniques used for sampling?

Cluster sampling also involves dividing the population into sub-populations, but each subpopulation should have analogous characteristics to that of the whole sample. Rather than sampling individuals from each subpopulation, you randomly select the entire subpopulation.


4. What is P-value?

P-values are used to make a decision about a hypothesis test. P-value is the minimum significant level at which you can reject the null hypothesis. The lower the p-value, the more likely you reject the null hypothesis.

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