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Scipy.stats.ttest_ind() function
- To perform a t-test in Python, you can use the scipy.stats.ttest_ind() function like t_statistic, p_value = stats.ttest_ind(data1, data2). This function allows you to compare two independent data sets and returns the t-statistic and the p-value.
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Feb 12, 2024 · In this post, you’ll learn how to perform t-tests in Python using the popular SciPy library. T-tests are used to test for statistical significance and can be hugely advantageous when working with smaller sample sizes.
Jul 25, 2023 · In this article, we will discuss the assumptions of a t-test, its benefits when using Python and how to perform various types of t-tests in Python with examples. We will also provide troubleshooting tips for using t-tests in Python.
- Machine Learning Engineer
- 20 min
- 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...
Aug 8, 2019 · The t statistic calculated by the test can be interpreted by comparing it to critical values from the t-distribution. The critical value can be calculated using the degrees of freedom and a significance level with the percent point function (PPF).
One of the most common problems in statistics is comparing the means between two populations. The most common approach to this is the t-test. In this article, we will discuss about this popular statistical test and show some simple examples in the Python programming language.
May 11, 2022 · The following code shows how to enter the scores of each student in a pandas DataFrame and then use the ttest_ind () function from the SciPy library to perform an independent two sample t-test: import pandas as pd. from scipy.stats import ttest_ind. #create pandas DataFrame.
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.
