Complete Hypothesis Testing Playlist - [ Ссылка ]
References:
Normal Distribution - [ Ссылка ]
One Sample Z test - [ Ссылка ]
Welcome to our comprehensive video on the one sample z-test for proportions! In this tutorial, we introduce the intricacies of this statistical test and explore its application in solving real-world problems.
In this video, we begin by explaining the key differences between a routine one sample z-test and the one sample z-test for proportions. Understanding these distinctions is essential for grasping the underlying concepts and their practical implications.
We then look into the assumptions involved in the one sample z-test for proportions. By understanding these assumptions, you will gain a solid foundation for conducting accurate and reliable statistical analyses.
To demonstrate the practicality of this test, we present an engaging e-commerce problem statement. Through a step-by-step approach, we guide you on how to calculate the test statistic manually, allowing you to understand the inner workings of the test.
Additionally, we showcase how to leverage the power of the statsmodels library in Python to perform the one sample z-test for proportions effortlessly. By comparing the manual calculations with the library's proportions_ztest function, we shed light on potential discrepancies arising from certain library-specific modifications in calculating the standard error.
Our goal is to provide you with a complete understanding of the one sample z-test for proportions, empowering you to apply this statistical tool effectively in various scenarios.
Happy Learning!
#Statistics #HypothesisTesting #Proportions #DataAnalysis #Ecommerce #Python
