Is probability and statistics for Data Science asked in interviews?

Probability and statistics are very important aspects in data science. One may not be as valuable as the other, but they both are crucial. Statistics however, is at the core of sophisticated machine learning algorithms. And we all know how big machine learning is in data science.

From an interview aspect, it depends on what kind of role you are applying to. Because depending on the job role, the questions will be modified accordingly. Take artificial intelligence (AI) as an example. If you are applying to such a role that is heavily concerned with AI, questions regarding machine learning will definitely be a part of it. Hence, there will be statistics questions there.

In data science, statistics is used to gather, review, analyze, and draw conclusions from data. But that’s it all. It is also used to apply quantified mathematical models to appropriate variables. These tasks are very much niche to some of the popular jobs in data science. Based on these things, anyone can predict that you will need a proper understanding of statistics in data science.

Probability on the other hand is a mathematical foundation of statistical inference. Probability is indispensable for analyzing affected data by chance. If you think carefully, this is like trying to find information on not a set basis. There are a lot of data structures used in data science. If you don't have tools like probability you will be forced to find values by yourself going over every piece of information.

Probability may not be used as much as statistics in data science, but it has its positions. In a data science interview for a master program, you don’t need much expertise. The interview committee simply wishes to learn your capabilities here as you will be learning the subject itself. However, for a job in data science interview, these basics are important.

For both serious tough, I suggest you to learn following statistics topics -

• Measure of center and spreads (mean, variance, standard deviation)
• Inferential statistics
• Bayes’ theorem

Similarly, go over these topics in probability -

• Independent and dependent events
• Permutations and combinations
• Probability distribution

 

I hope I offered rough information to clear your doubts. Does this help you need some more specific insights? Let me know if I can help any way possible.