Online sourses to learn chi square test of homogeneity

In summary, the conversation discusses the topic of chi square test of homogeneity and the differences in how it is approached in different sources. The main question is whether the process mentioned in a particular book is incorrect, as it involves subtracting a second X2 from the original one. Relevant sources for learning about chi square test of homogeneity are mentioned, including an online statistics course and university websites.
  • #1
Tyto alba
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I want to study chi square test of homogeneity from any authentic source- book / website especially problems where samples are compared for more than one attribute.

Chi square test of homogeneity is a Chi square test that determines whether two or more independent random samples are from the same or different population.

What are some relevant sources?

Relevant background:

I was studying examples from random online sources before I saw this book in which a second X2
has been calculated and has been substracted from the principle X
2 (the one we usually find). This is inconsistent to the examples I saw online.
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Infact we are being taught the latter process.
 
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  • #2
This may help, it's an online statistics course. The second to last section covers chi square. I'm giving you the whole table of contents in case you need to review other videos in the course.

https://dl.dropboxusercontent.com/u/28928849/Webpages/Statistics_OnlineStatBook.html
 
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  • #3
I checked your recommended Rice University video on Homogeneity. I also went through a number of other university websites (and videos) and all of them have solved homogeneity in the line of test of independence which appears very semantic to me. I was wondering if the process mentioned in my book (snip offs in OP) is wrong. I couldn't understand what was the need to subtract the usual X2 from the X2 obtained from adding the data points of a particular category (here yellow and green seeds) as the author has done.
 

1. What is a chi square test of homogeneity?

A chi square test of homogeneity is a statistical test used to determine whether there is a significant difference in the distribution of categorical variables across multiple groups or categories.

2. How do I perform a chi square test of homogeneity?

To perform a chi square test of homogeneity, you will need to first organize your data into a contingency table. Then, you can use a statistical software or an online calculator to calculate the chi square statistic and the corresponding p-value. Based on the p-value, you can determine whether there is a significant difference in the distribution of your categorical variables.

3. What is the null hypothesis in a chi square test of homogeneity?

The null hypothesis in a chi square test of homogeneity is that there is no significant difference in the distribution of categorical variables across the groups or categories being compared. This means that any observed differences are due to chance and not a true difference between the groups.

4. What is the alternative hypothesis in a chi square test of homogeneity?

The alternative hypothesis in a chi square test of homogeneity is that there is a significant difference in the distribution of categorical variables across the groups or categories being compared. This means that the observed differences are not due to chance and there is a true difference between the groups.

5. When should I use a chi square test of homogeneity?

A chi square test of homogeneity is typically used when you have two or more categorical variables and you want to determine whether there is a significant difference in the distribution of these variables across groups or categories. It is commonly used in social science research to analyze survey data and in medical research to compare disease rates across different populations.

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