Statistics is the study of the collection, analysis, interpretation, presentation, and organisation of data. For all the data science and machine learning enthusiasts it is paramount to be well versed with various statistical concepts such as Hypothesis testing

Every day we find ourselves testing new ideas, finding the fastest route to the office, the quickest way to finish our work, or simply finding a better way to do something we love. The critical question, then, is whether our idea is significantly better than what we tried previously.

These ideas that we come up with on such a regular basis – that’s essentially what a hypothesis is. And testing these ideas to figure out which one works and which one is best left behind, is called hypothesis testing.

### Statistics is the Grammar of Data Science

#### The course is structured in a manner that you will get ample of examples in each module. You’ll get to learn all about

• Fundamentals of Hypothesis Testing: The course begins with a simple-to-understand example on hypothesis testing. This chapter will clear all your basics like - Null Hypothesis, Alternative Hypothesis, Type 1 Error, Type 2 Error, and Significance Level.

• p-value

• What is the Z Test? The course introduces the most basic type of testing a hypothesis - Z test. Z tests are a statistical way of testing. The chapter covers the one sample as well as the two sample Z test.

• What is the t-Test? The t-test is another test for validating the hypothesis. The chapter begins with a unique example and later covers both the one-sample and two-sample t-test.

• Deciding between the Z Test and t-Test Are you confused on how to use these tests? Don’t worry, the course comprises a simple step-by-step guide on choosing the best test for your experiment.

• Case Study: Hypothesis Testing for Coronavirus in Python You’ll get to put your theoretical knowledge into practice and see how well you can do. You will get to work on a hypothesis testing case study on the corona virus dataset in Python!

### Prerequisites for the Hypothesis Testing for Data Science and analytics

A basic knowledge of descriptive statistics like - mean, median, mode, variance and standard deviation. Experience in Python is a plus!

### Course curriculum

• 1
##### Introduction to the course
• Introduction to Hypothesis Testing Course
• 2
##### Fundamentals of Hypothesis Testing
• Understanding Hypothesis Testing
• Steps to Perform for Hypothesis testing
• Critical Value - p-value
• Directional Hypothesis
• Non-Directional Hypothesis
• 3
##### What is the Z Test?
• What is Z test?
• One-Sample Z test
• One-Sample Z test - Example
• Two-Sample Z Test
• Two-Sample Z Test - Example
• 4
##### What is the t-Test?
• What is t-test?
• One-Sample t-Test
• One Sample t-Test - Example
• Two-Sample t-Test
• Two-Sample t-Test - Example
• 5
##### Deciding between Z Test and T-Test
• Deciding between Z Test and T-Test
• 6
##### Case Study: Hypothesis Testing for Coronavirus using Python
• Two-Sample Z test for a Coronavirus Dataset

### FAQ

• You’ll get to put your theoretical knowledge into practice and see how well you can do. You will get to work on a hypothesis testing case study on the corona virus dataset in Python!

A working knowledge of basic statistics would be helpful. Even though we have designed this course for beginners, knowing a bit about basic statistics will help you visualize certain concepts in a more vivid manner.

• What is the fee for the course?

This course is free of cost.

• How much effort do I need to put in for this course?

You’ll be able to finish this course in a week’s time if you spend an hour on it daily and explore it on your own along with what you learn here.

• I’ve completed this course and have a good grasp on Hypothesis Testing. What should I learn next?

The next step in your journey is to build on what you’ve learned so far. There are plenty of options to choose from. We suggest heading to courses.analyticsvidhya.com and browsing through the various offerings available.
You should also incorporate hypothesis testing in your daily life! Try and use problem statements from around you and build hypotheses based on those/ That’s the best way to learn.

• Do I need to install any software as part of the course?

You will not require any software for the learning modules. Python and other libraries are necessary to solve the case study.

• How long can I access the course?

Once you register, you will have 6 months to complete the course. If you visit the course 6 months after your initial registration - you will need to enroll in the course again. Your past progress will be lost.