Using statistical models, we usually care a lot about uncertainty estimates (confidence intervals, hypothesis tests, etc.) When we are using machine learning models, we typically don’t make any substantial/par
You’ll probably be conducting the t-tests in a spreadsheet or statistical program (like Excel or SPSS). However, if you’d like to do the math by hand, the formulas for the other two types of t-tests are included below.2. Calculate the degrees of freedom...
We have discussed many statistical tests and tools in this series of commentaries, and while we have mentioned the underlying assumptions of the tests, we have not explored them in detail. We stop to look at some of the assumptions of the t-test and linear regression, justify and explain ...
The t-test and chi-square tests are statistical tests, t-test: A t-test is a parametric test which is used to test a null hypothesis about two... Learn more about this topic: Hypothesis Testing Definition, Steps & Examples from
What are the main types of statistical analysis? The two main types of statistical analysis are descriptive statistics (which summarizes the characteristics of given data) and inferential statistics (which draws conclusions about a larger population from given sample data). ...
What are the methods for analyzing split testing results? There are two main statistical analysis methods. The first is called a Student’s T-Test, and the second is known as a multi-armed bandit. The big benefit of using the multi-armed bandit approach is that you have a lot more flexi...
Practical significance and statistical significance are synonymous terms. Is the statement true or false? What is the difference between descriptive statistics and inferential statistics? Give an example of each. Explain how p-values that are 0.05, 0.049,...
Types of Statistical TestsIn terms of selecting a statistical test, the most important question is "what is the main study hypothesis?". For example, nQuery has a vast list of statistical procedures to calculate sample size, in fact over 1000 sample size scenarios are covered. However, it ...
The two are related disciplines, but there are distinct differences. Multivariate testing tests different content for multiple elements (vs. a single element in A/B testing) across one or more website pages or email marketing campaigns to identify the combination that yields the highest conversion...
Some teams may target 90% to reduce the sample size and speed up results, but this increases the risk of inaccurate findings. Several factors can prevent you from reaching statistical significance, including: Not enough time to run tests Pages with very low traffic Changes that are too small ...