Chapter 4. Statistical Concepts for Predictive Modelling
There are a few statistical concepts, such as hypothesis testing, p-values, normal distribution, correlation, and so on without which grasping the concepts and interpreting the results of predictive models becomes very difficult. Thus, it is very critical to understand these concepts, before we delve into the realm of predictive modelling.
In this chapter, we will be going through and learning these statistical concepts so that we can use them in the upcoming chapters. This chapter will cover the following topics:
- Random sampling and central limit theorem: Understanding the concept of random sampling through an example and illustrating the central limit theorem's application through an example. These two concepts form the backbone of hypothesis testing.
- Hypothesis testing: Understanding the meaning of the terms, such as null hypothesis, alternate hypothesis, confidence intervals, p-value, significance level, and so on...
