Chi-square Test for Independence
February 25, 2022
Key concepts for understanding the Test for Independence.
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Each of my blog posts are answers to questions my students have asked in my into stats classes. I try to keep my answers short and focused on the essential information the students need to know without diving too deep into theory. When I think it useful, I provide links to my Dr Dawn Wright blog where I go deeper to give more insight.
Key concepts for understanding the Test for Independence.
Chi-square tests are very useful in understanding relationships and proportions. This is a concise overview.
Key concepts of the Chi-square Test for Homogeneity – how it differs from the Test for Indpendence.
Key concepts in understanding the Chi-square Goodness of Fit test.
The logic behind why a two-tail p-value is always twice the one-tail value.
How to determine which side of the distribution to use in your hypothesis test.
Understanding p-value is often a challenge for stats students. Here is a focused explanation.
This is a student’s question about the NOIR acronym for the most common measurement scales. Here is my answer:
Picking the right distribution to use for your hypothesis test is important. For comparing means, we use either the z or the t-distribution. Here’s how to choose the right one.
Each of my blog posts are answers to questions my students have asked in my intro stats classes. I try to keep my answers short and focused on the essential information intro to intermediate stats students need to know without diving too deep into theory. Where I think it useful, I do have links to my Dr.Dawn. Wright blog where I go deeper into the topics to give more insight.
Key concepts for understanding the Test for Independence.
Chi-square tests are very useful in understanding relationships and proportions. This is a concise overview.
Key concepts of the Chi-square Test for Homogeneity – how it differs from the Test for Indpendence.
Key concepts in understanding the Chi-square Goodness of Fit test.