Step by Step Guide to understand Hypothesis Testing in Data Science using R
Step by Step Guide to understand Hypothesis Testing in Data Science using R
Before understanding Hypothesis Testing, let us understand this important equation Y=f(x).
In the above equation Y = Output, f(x) = Input.
Any output you want to get is depends on either one input or multiple input values.
Example 1: If you want to predict weight gain of a person (Output), it depends on Calories consumed(input).
Example 2 : If you want to predict price of a used car(output), it depends on Mileage, Year of manufacture, kilometers driven etc etc(Multiple inputs).
Now, let us understand Hypothesis Testing.
For example, lets assume a person who is accused is produced in the court and in reality that person is innocent.If the judge is going to release him, that is "Right Decision" which is written in 1-α which is 95% as a industry standard.
But if the judge imprisons that person even though he is innocent, that is wrong decision.This error is called Type 1 error and notation is α. Industry…
Before understanding Hypothesis Testing, let us understand this important equation Y=f(x).
In the above equation Y = Output, f(x) = Input.
Any output you want to get is depends on either one input or multiple input values.
Example 1: If you want to predict weight gain of a person (Output), it depends on Calories consumed(input).
Example 2 : If you want to predict price of a used car(output), it depends on Mileage, Year of manufacture, kilometers driven etc etc(Multiple inputs).
Now, let us understand Hypothesis Testing.
For example, lets assume a person who is accused is produced in the court and in reality that person is innocent.If the judge is going to release him, that is "Right Decision" which is written in 1-α which is 95% as a industry standard.
But if the judge imprisons that person even though he is innocent, that is wrong decision.This error is called Type 1 error and notation is α. Industry…