Chapter 4. Deep Dive into Inferential Statistics
Our world is a big data generating machine. These day-to-day activities consist of random and complex events that can be used to better understandUnivariate distributions: Normal, gamma, binomial the world. To achieve this, we will try to gain a deeper understanding of the processes.
Inferential statistics is to reach to a conclusion on the basis of evidence and reasoning gained from the sample data that is generalized for the population. Inferential statistics considers that there will be some sampling errors, which means the sample that we have drawn from the population may not be perfectly representing the population.
Inferential statistics include:
- Estimation
- Hypothesis testing
What is the difference between a sample and population? A population is a collection of all the events or observations about which we want want to gain knowledge. But its size can be so huge that it is not always convenient or feasible to analyze every event...
