This page represents a list of **questions** which can be used for preparation of **machine learning interviews**. The following are some of the areas covered in this set of questions:

- Null Hypothesis; Another page which explains the concept in decent manner is Null Hypothesis definition and examples, how to state.
- P-value; In simple words, p-value represents likelihood (in terms of probability) of sample results occurring if the null hypothesis is assumed to be true. For example, a p-value of 0.03 would mean that given the null hypothesis is true, the probability that results occur in the sample is 0.03 which is very less. Thus, the alternate hypothesis can be true. Thus, one can reject the null hypothesis.
- One-tailed vs Two-tailed tests; This is another page on one and two-tailed tests

#### Rejecting null hypothesis implies that there is an association between two measured entities?

#### Given two samples taken from the same population, a stronger null hypothesis would mean _______?

#### P-value less than ________ would mean that null hypothesis can be rejected.

### 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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