Hypothesis Testing: Introduction(Udemy Statistics for Data Science and Business Analysis)

Question 1

What are the 4 steps in data driven decision making?

Answer 1

1. Formulate a hypothesis
   2.Find the right test
   3.Execute the test
   4.Make a decision

Question 2

What is a hypothesis?

Answer 2

A hypothesis is an idea that can be tested

Question 3

What is alpha?

Answer 3

The probability of rejecting the null hypothesis, if it is true

Question 4

What makes you select a certain alpha?

Answer 4

It is a value that you select based on the certainty that you need

Question 5

What is a one sided test?

Answer 5

The whole rejection region would only be on one side of the distribution, the right or the left, rather than on either side like in a two sided test

Question 6

What are the types of errors in hypothesis testing?

Answer 6

Type I and Type II Error

Question 7

What is a type I Error and what is it also called?

Answer 7

When you reject a true null hypothesis, also called a false positive

Question 8

What is a type II Error and what is it called?

Answer 8

When you accept a false null hypothesis, a false negative

Question 9

What is the Power of a test?

Answer 9

It is the probability that it will correctly lead to the rejection of the null hypothesis when it is false, it is the ability of a test to detect an effect, if an effect actually exists