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Feb 12, 2024 · T-tests are used to test for statistical significance and can be hugely advantageous when working with smaller sample sizes. By the end of this tutorial, you’ll have learned the following: What the different t-tests are and when they should be applied. How to perform a one-sample t-test and a two-sample t-test in Python.
- Terminology Explained
- T-test Assumptions
- One-Sample t-test
- How to Perform Two-Sample t-test in Python
- How to Perform Paired t-test in Python
- How to Perform Welch's t-test in Python
- Conclusion
- References and Recommended Resources
Before we delve deeper into the details of the t-test, let us quickly understand some of the associated terminologies that will help strengthen your conceptual grasp of this statistical test.
Understanding the assumptions of a statistical test is crucial to ensure accurate and reliable results. The t-test is no exception. Any violation of its assumptions could lead to misleading conclusions, which would be counterproductive. Let's explore the four assumptions of the t-test in detail:
The one-sample t-test is a statistical hypothesis test that helps determine if an unknown population mean (mu) does not equal a claimed value. Where, x = sample mean 𝝁 = population mean S = sample standard deviation n = number of examples in the sample t = t-statistic Let’s understand this by using an example. A company claims to produce ball bear...
Let’s extend our example by assuming that the company sets up another factory to produce identical ball bearings. We need to find out if the ball bearings from the two factories are of different sizes. For such a scenario, we use the two-sample test. Here the t-statistic is defined as below. Where, X1= first sample mean X2 = second sample mean S1= ...
Upon sharing these results with the company, it decides to improve its manufacturing technology by introducing a new casting machine. It starts this pilot from one of the factories and conducts a test to identify if the new casting machine leads to a change in the diameter of the bearings by comparing two samples of 25 bearings – one before the new...
After a successful pilot from the new casting machine at one factory, the company wants to try another pilot at its second factory with a new rubbing machine. This machine is known to produce highly accurate ball bearings but is affected by temperature changes and power fluctuations. The company needs to identify if the ball bearings from the two f...
Data has the power to uncover the true underlying phenomenon impacting business decisions only if interrogated rightly. It requires a robust understanding of different statistical tests to know which one to apply and when. This tutorial focuses on t-tests and explains their underlying assumptions, such as independent and identically distributed obs...
Jul 25, 2023 · A t-test is a statistical method that determines whether there is a significant difference between the means of two groups. There are several Python libraries available to conduct a T-test, including SciPy and NumPy.
- Machine Learning Engineer
- 20 min
The objective of this test is to compare the means of two related or unrelated sample groups. It is used in hypothesis testing to test the applicability of an assumption to a population of interest. T-tests are only applicable to two data groups.
T-tests are used to determine if there is significant deference between means of two variables and lets us know if they belong to the same distribution.
Jun 15, 2023 · What is a t-test? A t-test is one of the most common ways to test a hypothesis, and we use it to test two means against each other. We run a t-test when we have one or two samples, we...
Aug 19, 2022 · T test in Python is a statistical method to test any hypothesis. Moreover, It helps you validate your study in terms of statistical values. There are three types of T-tests you can perform, and we are going to cover all three and their implementation in Python.
