Summary

In this chapter, we skimmed through the basic concepts of statistics. Here is a brief summary of the concepts we learned:

• Hypothesis testing is used to test the statistical significance of a hypothesis. The one which already exists or is assumed to be true is a null hypothesis, the one which someone is not sure about or is being proposed as an alternate premise is an alternate hypothesis.
• One needs to calculate a statistic and the associated p-value to conduct the test.
• Hypothesis testing (p-values) is used to test the significance of the estimates of the coefficients calculated by the model.
• The chi-square test is used to test the causal relationship between a predictor and an input variable. It can also be used to check whether the data is fair or fake.
• The correlation coefficient can range from -1 to 1. The closer it is to the extremes, the stronger is the relationship between the two variables.

Linear regression is part of the family of algorithms called supervised algorithms as the...